Low solar spectrum coverage,high evaporation enthalpy,and undesired salt deposition severely limited the solar-driven interfacial evaporation technology for further sewage purification and seawater desalination.To ove...Low solar spectrum coverage,high evaporation enthalpy,and undesired salt deposition severely limited the solar-driven interfacial evaporation technology for further sewage purification and seawater desalination.To overcome these problems,we designed an amphiphilic Janus-structured polyaniline(PANI)/ZrC/cellulose acetate(CA)(J-PZCA) membrane.Firstly,the interfacial interaction between PANI and ZrC enhances the photoabsorption and photothermal conversion efficiency.Secondly,low thermal conductivity reduces the heat lost at the interface.Most importantly,ZrC could facilitate interfacial activation,which weakens the intermolecular forces of water by affecting the hydrogen bond.Under 1 solar irradiation(1 sun),the composite membrane exhibits a high evaporation rate of 1.31 kg m^(-2)h^(-1) and an excellent efficiency of 79.4%.In addition,the sewage purification and seawater desalination experiments reveal a remarkable purification capability of J-PZCA membrane.Especially for the treatment of high-concentration salt solution,it realizes a long-term stable evaporation performance due to the excellent salt deposition resistance.Therefore,the J-PZCA membrane constructed in this study provides a new perspective for the design of efficient interfacial evaporation devices.展开更多
We present a general machine learning based scheme to optimize experimental control.The method utilizes the neural network to learn the relation between the control parameters and the control goal,with which the optim...We present a general machine learning based scheme to optimize experimental control.The method utilizes the neural network to learn the relation between the control parameters and the control goal,with which the optimal control parameters can be obtained.The main challenge of this approach is that the labeled data obtained from experiments are not abundant.The central idea of our scheme is to use the active learning to overcome this difficulty.As a demonstration example,we apply our method to control evaporative cooling experiments in cold atoms.We have first tested our method with simulated data and then applied our method to real experiments.It is demonstrated that our method can successfully reach the best performance within hundreds of experimental runs.Our method does not require knowledge of the experimental system as a prior and is universal for experimental control in different systems.展开更多
The key pose frames of a human motion pose sequence,play an important role in the compression,retrieval and semantic analysis of continuous human motion.The current available clustering methods in literatures are diff...The key pose frames of a human motion pose sequence,play an important role in the compression,retrieval and semantic analysis of continuous human motion.The current available clustering methods in literatures are difficult to determine the number of key pose frames automatically,and may destroy the postures’ temporal relationships while extracting key frames.To deal with this problem,this paper proposes a new key pose frames extraction method on the basis of 3D space distances of joint points and the improved X-means clustering algorithm.According to the proposed extraction method,the final key pose frame sequence could be obtained by describing the posture of human body with space distance of particular joint points and then the time-constraint X-mean algorithm is applied to cluster and filtrate the posture sequence.The experimental results show that the proposed method can automatically determine the number of key frames and save the temporal characteristics of motion frames according to the motion pose sequence.展开更多
基金supported by the National Natural Science Foundation of China (52172278)Interdisciplinary Research Foundation of HIT (IR2021103)。
文摘Low solar spectrum coverage,high evaporation enthalpy,and undesired salt deposition severely limited the solar-driven interfacial evaporation technology for further sewage purification and seawater desalination.To overcome these problems,we designed an amphiphilic Janus-structured polyaniline(PANI)/ZrC/cellulose acetate(CA)(J-PZCA) membrane.Firstly,the interfacial interaction between PANI and ZrC enhances the photoabsorption and photothermal conversion efficiency.Secondly,low thermal conductivity reduces the heat lost at the interface.Most importantly,ZrC could facilitate interfacial activation,which weakens the intermolecular forces of water by affecting the hydrogen bond.Under 1 solar irradiation(1 sun),the composite membrane exhibits a high evaporation rate of 1.31 kg m^(-2)h^(-1) and an excellent efficiency of 79.4%.In addition,the sewage purification and seawater desalination experiments reveal a remarkable purification capability of J-PZCA membrane.Especially for the treatment of high-concentration salt solution,it realizes a long-term stable evaporation performance due to the excellent salt deposition resistance.Therefore,the J-PZCA membrane constructed in this study provides a new perspective for the design of efficient interfacial evaporation devices.
基金Supported by the Beijing Outstanding Young Scientist Program(HZ)the National Key R&D Program of China(Grant Nos.2016YFA0301600, 2016YFA0301602, and 2018YFA0307600)the National Natural Science Foundation of China(Grant Nos.11734010 and 11804203)
文摘We present a general machine learning based scheme to optimize experimental control.The method utilizes the neural network to learn the relation between the control parameters and the control goal,with which the optimal control parameters can be obtained.The main challenge of this approach is that the labeled data obtained from experiments are not abundant.The central idea of our scheme is to use the active learning to overcome this difficulty.As a demonstration example,we apply our method to control evaporative cooling experiments in cold atoms.We have first tested our method with simulated data and then applied our method to real experiments.It is demonstrated that our method can successfully reach the best performance within hundreds of experimental runs.Our method does not require knowledge of the experimental system as a prior and is universal for experimental control in different systems.
基金Supported by the National Natural Science Foundation of China(61303127)Project of Science and Technology Department of Sichuan Province(2014SZ0223,2014GZ0100,2015GZ0212)+1 种基金Key Program of Education Department of Sichuan Province(11ZA130,13ZA0169)Postgraduate Innovation Fund Project by Southwest University of Science and Technology(15ycx057)
文摘The key pose frames of a human motion pose sequence,play an important role in the compression,retrieval and semantic analysis of continuous human motion.The current available clustering methods in literatures are difficult to determine the number of key pose frames automatically,and may destroy the postures’ temporal relationships while extracting key frames.To deal with this problem,this paper proposes a new key pose frames extraction method on the basis of 3D space distances of joint points and the improved X-means clustering algorithm.According to the proposed extraction method,the final key pose frame sequence could be obtained by describing the posture of human body with space distance of particular joint points and then the time-constraint X-mean algorithm is applied to cluster and filtrate the posture sequence.The experimental results show that the proposed method can automatically determine the number of key frames and save the temporal characteristics of motion frames according to the motion pose sequence.
