The osteochondral defect repair has been most extensively studied due to the rising demand for new therapies to diseases such as osteoarthritis.Tissue engineering has been proposed as a promising strategy to meet the ...The osteochondral defect repair has been most extensively studied due to the rising demand for new therapies to diseases such as osteoarthritis.Tissue engineering has been proposed as a promising strategy to meet the demand of simultaneous regeneration of both cartilage and subchondral bone by constructing integrated gradient tissue-engineered osteochondral scaffold(IGTEOS).This review brought forward the main challenges of establishing a satisfactory IGTEOS from the perspectives of the complexity of physiology and microenvironment of osteochondral tissue,and the limitations of obtaining the desired and required scaffold.Then,we comprehensively discussed and summarized the current tissue-engineered efforts to resolve the above challenges,including architecture strategies,fabrication techniques and in vitro/in vivo evaluation methods of the IGTEOS.Especially,we highlighted the advantages and limitations of various fabrication techniques of IGTEOS,and common cases of IGTEOS application.Finally,based on the above challenges and current research progress,we analyzed in details the future perspectives of tissue-engineered osteochondral construct,so as to achieve the perfect reconstruction of the cartilaginous and osseous layers of osteochondral tissue simultaneously.This comprehensive and instructive review could provide deep insights into our current understanding of IGTEOS.展开更多
The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES)has the characteristics of strong coupling,non-convexity,and nonlinearity.The centralized optimization method has a high co...The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES)has the characteristics of strong coupling,non-convexity,and nonlinearity.The centralized optimization method has a high cost of communication and complex modeling.Meanwhile,the traditional numerical iterative solution cannot deal with uncertainty and solution efficiency,which is difficult to apply online.For the coordinated optimization problem of the electricity-gas-heat IES in this study,we constructed a model for the distributed IES with a dynamic distribution factor and transformed the centralized optimization problem into a distributed optimization problem in the multi-agent reinforcement learning environment using multi-agent deep deterministic policy gradient.Introducing the dynamic distribution factor allows the system to consider the impact of changes in real-time supply and demand on system optimization,dynamically coordinating different energy sources for complementary utilization and effectively improving the system economy.Compared with centralized optimization,the distributed model with multiple decision centers can achieve similar results while easing the pressure on system communication.The proposed method considers the dual uncertainty of renewable energy and load in the training.Compared with the traditional iterative solution method,it can better cope with uncertainty and realize real-time decision making of the system,which is conducive to the online application.Finally,we verify the effectiveness of the proposed method using an example of an IES coupled with three energy hub agents.展开更多
Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy couplin...Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy coupling equipment,and renewable energy.An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost,carbon emission and enhance the power supply reliability.Firstly,the lowcarbon mathematical model of combined thermal and power unit,carbon capture system and power to gas unit(CCP)is established.Subsequently,we establish a low carbon multi-objective optimization model considering system operation cost,carbon emissions cost,integrated demand response,wind and photovoltaic curtailment,and load shedding costs.Furthermore,considering the intermittency of wind power generation and the flexibility of load demand,the low carbon economic dispatch problem is modeled as a Markov decision process.The twin delayed deep deterministic policy gradient(TD3)algorithm is used to solve the complex scheduling problem.The effectiveness of the proposed method is verified in the simulation case studies.Compared with TD3,SAC,A3C,DDPG and DQN algorithms,the operating cost is reduced by 8.6%,4.3%,6.1%and 8.0%.展开更多
An infinite slope stability numerical model driven by the comprehensive physically-based integrated hydrology model(InHM) is presented.In this approach,the failure plane is assumed to be parallel to the hydraulic grad...An infinite slope stability numerical model driven by the comprehensive physically-based integrated hydrology model(InHM) is presented.In this approach,the failure plane is assumed to be parallel to the hydraulic gradient instead of the slope surface.The method helps with irregularities in complex terrain since depressions and flat areas are allowed in the model.The present model has been tested for two synthetic single slopes and a small catchment in the Mettman Ridge study area in Oregon,United States,to estimate the shallow landslide susceptibility.The results show that the present approach can reduce the simulation error of hydrological factors caused by the rolling topography and depressions,and is capable of estimating spatial-temporal variations for landslide susceptibilities at simple slopes as well as at catchment scale,providing a valuable tool for the prediction of shallow landslides.展开更多
In order to investigate the correlation between reactor performance and the microorganisms,an integrated A/O reactor was operated for 72 days to treat diluted livestock wastewater.Chemical oxygen demand （COD） remova...In order to investigate the correlation between reactor performance and the microorganisms,an integrated A/O reactor was operated for 72 days to treat diluted livestock wastewater.Chemical oxygen demand （COD） removal efficiency increased from 79% to 94%,with total nitrogen （TN） removal efficiency from 37% to 50% （HRT 7.4 hr） when the influent COD and TN were ca.1500 mg/L and 95 mg/L,respectively,and the outlet COD concentration was less than 100 mg/L at the end.Microbial community was monitored during start-up period by denaturing gradient gel electrophoresis （DGGE） based on 16S rRNA gene.DGGE profiles showed that microbial community had changed significantly during the start-up and these shifts were in accordance with the reactor performance.UPGMA clustering analysis showed that 14 anaerobic samples fell into five main groups and so did the aerobic ones,but the grouping patterns were different.Phylogenetic analysis indicated that microbial populations in the anaerobic compartment belonged to Firmicutes,Proteobacteria,Chloroflexi and Bacteroidetes,while Proteobacteria,Bacteroidetes,Firmicutes,Verrucomicrobiae and Nitrospira were present in the aerobic compartment.In the anaerobic compartment,more fermentative and acetogenic bacteria were detected during the start-up while denitrifying bacteria faded away.Two functional populations such as Nitrospira defluvii and Dechloromonas denitrificans were observed when nitrogen removal was high,indicating that simultaneous nitrification and denitrification occurred in the aerobic compartment.展开更多
基金support from the National Natural Science Foundation of China(No.32171345)Hebei Provincial Natural Science Foundation of China(No.C2022104003)+2 种基金the Fok Ying Tung Education Foundation(No.141039)the Fund of Key Laboratory of Advanced Materials of Ministry of Education,the International Joint Research Center of Aerospace Biotechnology and Medical Engineering,Ministry of Science and Technology of Chinathe 111 Project(No.B13003).
文摘The osteochondral defect repair has been most extensively studied due to the rising demand for new therapies to diseases such as osteoarthritis.Tissue engineering has been proposed as a promising strategy to meet the demand of simultaneous regeneration of both cartilage and subchondral bone by constructing integrated gradient tissue-engineered osteochondral scaffold(IGTEOS).This review brought forward the main challenges of establishing a satisfactory IGTEOS from the perspectives of the complexity of physiology and microenvironment of osteochondral tissue,and the limitations of obtaining the desired and required scaffold.Then,we comprehensively discussed and summarized the current tissue-engineered efforts to resolve the above challenges,including architecture strategies,fabrication techniques and in vitro/in vivo evaluation methods of the IGTEOS.Especially,we highlighted the advantages and limitations of various fabrication techniques of IGTEOS,and common cases of IGTEOS application.Finally,based on the above challenges and current research progress,we analyzed in details the future perspectives of tissue-engineered osteochondral construct,so as to achieve the perfect reconstruction of the cartilaginous and osseous layers of osteochondral tissue simultaneously.This comprehensive and instructive review could provide deep insights into our current understanding of IGTEOS.
基金supported by The National Key R&D Program of China(2020YFB0905900):Research on artificial intelligence application of power internet of things.
文摘The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES)has the characteristics of strong coupling,non-convexity,and nonlinearity.The centralized optimization method has a high cost of communication and complex modeling.Meanwhile,the traditional numerical iterative solution cannot deal with uncertainty and solution efficiency,which is difficult to apply online.For the coordinated optimization problem of the electricity-gas-heat IES in this study,we constructed a model for the distributed IES with a dynamic distribution factor and transformed the centralized optimization problem into a distributed optimization problem in the multi-agent reinforcement learning environment using multi-agent deep deterministic policy gradient.Introducing the dynamic distribution factor allows the system to consider the impact of changes in real-time supply and demand on system optimization,dynamically coordinating different energy sources for complementary utilization and effectively improving the system economy.Compared with centralized optimization,the distributed model with multiple decision centers can achieve similar results while easing the pressure on system communication.The proposed method considers the dual uncertainty of renewable energy and load in the training.Compared with the traditional iterative solution method,it can better cope with uncertainty and realize real-time decision making of the system,which is conducive to the online application.Finally,we verify the effectiveness of the proposed method using an example of an IES coupled with three energy hub agents.
基金supported in part by the Scientific Research Fund of Liaoning Provincial Education Department under Grant LQGD2019005in part by the Doctoral Start-up Foundation of Liaoning Province under Grant 2020-BS-141.
文摘Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy coupling equipment,and renewable energy.An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost,carbon emission and enhance the power supply reliability.Firstly,the lowcarbon mathematical model of combined thermal and power unit,carbon capture system and power to gas unit(CCP)is established.Subsequently,we establish a low carbon multi-objective optimization model considering system operation cost,carbon emissions cost,integrated demand response,wind and photovoltaic curtailment,and load shedding costs.Furthermore,considering the intermittency of wind power generation and the flexibility of load demand,the low carbon economic dispatch problem is modeled as a Markov decision process.The twin delayed deep deterministic policy gradient(TD3)algorithm is used to solve the complex scheduling problem.The effectiveness of the proposed method is verified in the simulation case studies.Compared with TD3,SAC,A3C,DDPG and DQN algorithms,the operating cost is reduced by 8.6%,4.3%,6.1%and 8.0%.
基金Project supported by the National Basic Research Program (973) of China (No 2011CB409901-01)the Foundation of Science and Technology Department of Zhejiang Province (No 2009C33117), China
文摘An infinite slope stability numerical model driven by the comprehensive physically-based integrated hydrology model(InHM) is presented.In this approach,the failure plane is assumed to be parallel to the hydraulic gradient instead of the slope surface.The method helps with irregularities in complex terrain since depressions and flat areas are allowed in the model.The present model has been tested for two synthetic single slopes and a small catchment in the Mettman Ridge study area in Oregon,United States,to estimate the shallow landslide susceptibility.The results show that the present approach can reduce the simulation error of hydrological factors caused by the rolling topography and depressions,and is capable of estimating spatial-temporal variations for landslide susceptibilities at simple slopes as well as at catchment scale,providing a valuable tool for the prediction of shallow landslides.
基金supported by the National Postdoctoral Fundation of China (No. 20070410881)the National Natural Science Fundation of China (No. 50878063)the National Natural Science Key Fundation of China (No.50638020)
文摘In order to investigate the correlation between reactor performance and the microorganisms,an integrated A/O reactor was operated for 72 days to treat diluted livestock wastewater.Chemical oxygen demand （COD） removal efficiency increased from 79% to 94%,with total nitrogen （TN） removal efficiency from 37% to 50% （HRT 7.4 hr） when the influent COD and TN were ca.1500 mg/L and 95 mg/L,respectively,and the outlet COD concentration was less than 100 mg/L at the end.Microbial community was monitored during start-up period by denaturing gradient gel electrophoresis （DGGE） based on 16S rRNA gene.DGGE profiles showed that microbial community had changed significantly during the start-up and these shifts were in accordance with the reactor performance.UPGMA clustering analysis showed that 14 anaerobic samples fell into five main groups and so did the aerobic ones,but the grouping patterns were different.Phylogenetic analysis indicated that microbial populations in the anaerobic compartment belonged to Firmicutes,Proteobacteria,Chloroflexi and Bacteroidetes,while Proteobacteria,Bacteroidetes,Firmicutes,Verrucomicrobiae and Nitrospira were present in the aerobic compartment.In the anaerobic compartment,more fermentative and acetogenic bacteria were detected during the start-up while denitrifying bacteria faded away.Two functional populations such as Nitrospira defluvii and Dechloromonas denitrificans were observed when nitrogen removal was high,indicating that simultaneous nitrification and denitrification occurred in the aerobic compartment.
