Molecular sieve catalysts,owing to their unique chemical properties,are widely used as catalysts among various catalytic reactions.Abundant Br?nsted acid sites in molecular sieve catalysts usually enable active compon...Molecular sieve catalysts,owing to their unique chemical properties,are widely used as catalysts among various catalytic reactions.Abundant Br?nsted acid sites in molecular sieve catalysts usually enable active components to disperse well on the catalyst surface,and help to adsorb a large number of gas molecules to achieve maximum catalytic performance.Therefore,a variety of molecular sieve catalysts have been developed and used in the selective catalytic reduction of NO_(x)by NH_(3)(NH_(3)-SCR).For example,Cu molecular sieve catalysts such as Cu-SSZ-13 and Cu-SAPO-34 with wide temperature windows and stable structure are considered and applied as commercial catalysts for NO_(x)removal in diesel vehicles for a long time.Although molecular sieve catalysts possess many advantages,they still cannot avoid the serious deactivation caused by various factors in practical applications.In this review,reasons leading to the deactivation of molecular sieve catalysts for NO_(x)reduction in actual working conditions were concluded.The deactivation mechanisms of molecular sieve catalysts for NO_(x)reduction were analyzed and the corresponding anti-deactivation strategies were summarized.Finally,challenges and prospects of molecular sieve catalysts for NO_(x)reduction were also proposed.展开更多
Although industrial processes often perform perfectly under design conditions, they may deviate from the optimal operating point owing to parameters drift, environmental disturbances, etc. Thus, it is necessary to dev...Although industrial processes often perform perfectly under design conditions, they may deviate from the optimal operating point owing to parameters drift, environmental disturbances, etc. Thus, it is necessary to develop efficacious strategies or procedure to assess the process performance online. In this paper, we explore the issue of operating optimality assessment for complex industrial processes based on performance-similarity considering nonlinearities and outliers simultaneously, and a general enforced online performance assessment framework is proposed. In the offline part, a new and modified total robust kernel projection to latent structures algorithm,T-KPRM, is proposed and used to evaluate the complex nonlinear industrial process, which can effectively extract the optimal-index-related process variation information from process data and establish assessment models for each performance grades overcoming the effects of outlier. In the online part, the online assessment results can be obtained by calculating the similarity between the online data from a sliding window and each of the performance grades. Furthermore, in order to improve the accuracy of online assessment, we propose an online assessment strategy taking account of the effects of noise and process uncertainties. The Euclidean distance between the sliding data window and the optimal evaluation level is employed to measure the contribution rates of variables, which indicate the possible reason for the non-optimal operating performance. The proposed framework is tested on a real industrial case: dense medium coal preparation process, and the results shows the efficiency of the proposed method comparing to the existing method.展开更多
Objective:To investigate the effect of Chinese massage combined with warm acupuncture on knee osteoarthritis.Methods:60 patients with knee osteoarthritis who were treated in our hospital from January 2017 to October 2...Objective:To investigate the effect of Chinese massage combined with warm acupuncture on knee osteoarthritis.Methods:60 patients with knee osteoarthritis who were treated in our hospital from January 2017 to October 2019 were selected as the research subjects,and they were randomly divided into 2 groups of 30 patients each.The control group was treated with oral western medicine,and the observation group was treated with massage combined with warm acupuncture.The clinical efficacy and WOMAC index were compared between the two groups.Results:The total effective rate of the observation group was higher than that of the control group,and the WOMAC score was lower than that of the control group.The difference was statistically significant(P<0.05).Conclusion:Chinese massage combined with warm acupuncture is effective in treating knee osteoarthritis It can effectively alleviate the symptoms of pain and joint stiffness in patients,and improve joint mobility,which is worth for clinical promotion.展开更多
The formation of multiple oxygen intermediates supporting efficient oxygen evolution reaction(OER)are affinitive with hydroxyl adsorption.However,ability of the catalyst to capture hydroxyl and maintain the continuous...The formation of multiple oxygen intermediates supporting efficient oxygen evolution reaction(OER)are affinitive with hydroxyl adsorption.However,ability of the catalyst to capture hydroxyl and maintain the continuous supply at active sits remains a tremendous challenge.Herein,an affordable Ni2P/FeP2 heterostructure is presented to form the internal polarization field(IPF),arising hydroxyl spillover(HOSo)during OER.Facilitated by IPF,the oriented HOSo from FeP2 to Ni2P can activate the Ni site with a new hydroxyl transmission channel and build the optimized reaction path of oxygen intermediates for lower adsorption energy,boosting the OER activity(242 mV vs.RHE at 100 mA cm-2)for least 100 h.More interestingly,for the anion exchange membrane water electrolyzer(AEMWE)with low concentration electrolyte,the advantage of HOSo effect is significantly amplified,delivering 1 A cm^(-2)at a low cell voltage of 1.88 V with excellent stability for over 50 h.展开更多
Although reinforcement learning(RL)has shown great potential in industrial process coordinated optimization,its direct application to complex scheduling tasks such as the thickening-dewatering process is still limited...Although reinforcement learning(RL)has shown great potential in industrial process coordinated optimization,its direct application to complex scheduling tasks such as the thickening-dewatering process is still limited by challenges including low sample efficiency and slow convergence.In this work,we propose an expert-augmented dual-stage reinforcement learning(EADS-RL)framework.In the first stage,expert data extracted from real industrial operation logs are used to pre-train both the policy and critic networks via imitation learning(IL),aiming to provide the agent with a reliable initial policy and thus accelerate the learning process.In the subsequent online RL optimization stage,EADS-RL effectively integrates expert priors and high-quality online experiences through a non-parametric regression model and a dynamic expert memory.The former offers reliable behavioral guidance for the agent to explore unknown state spaces,thereby improving exploration efficiency;the latter enables the expert memory to evolve by incorporating excellent trajectories discovered by the agent itself,facilitating continuous self-improvement of the policy.The simulation results demonstrate that EADS-RL significantly outperforms existing benchmark algorithms in terms of both convergence speed and final performance.In scheduling task evaluations,the proposed method not only achieves the lowest energy consumption but also attains the highest key process indicator(underflow concentration),while ensuring safe and stable process operation.These results highlight the substantial potential of EADS-RL for practical industrial applications.展开更多
The existence and multiplicity of positive solutions to a periodic boundary value problem for nonlinear third-order ordinary differential equation are established,based on the zero point theorem concerning cone expans...The existence and multiplicity of positive solutions to a periodic boundary value problem for nonlinear third-order ordinary differential equation are established,based on the zero point theorem concerning cone expansion and compression of order type.Our main approach is different from the previous papers on the existence of multiple positive solutions to the similar problem.展开更多
It gives us great pleasure to announce the launch of the Journal of Control and Decision(JCD).The primary aim of the journal is to provide a platform for scientists,engineers and practitioners throughout the world to ...It gives us great pleasure to announce the launch of the Journal of Control and Decision(JCD).The primary aim of the journal is to provide a platform for scientists,engineers and practitioners throughout the world to present the latest advancement in Control,Decision,Automation,Robotics and Emerging Technologies.The journal publishes original contributions in both theory and applications,comprehensive technical reviews,survey papers and book reviews in all the areas of these disciplines.JCD is published quarterly by Taylor&Francis Group,UK.It has a strong editorial board team consisting of well-established researchers with vast professional experiences in various areas of the journal.All submitted papers will be reviewed on a peer review basis and handled by the editorial board of the journal.Only high-quality papers will be accepted for publication.展开更多
基金the support from the National Natural Science Foundation of China(No.22125604)the Chenguang Program supported by Shanghai Education Development Foundation and Shanghai Municipal Education Commission(No.22Z00354)。
文摘Molecular sieve catalysts,owing to their unique chemical properties,are widely used as catalysts among various catalytic reactions.Abundant Br?nsted acid sites in molecular sieve catalysts usually enable active components to disperse well on the catalyst surface,and help to adsorb a large number of gas molecules to achieve maximum catalytic performance.Therefore,a variety of molecular sieve catalysts have been developed and used in the selective catalytic reduction of NO_(x)by NH_(3)(NH_(3)-SCR).For example,Cu molecular sieve catalysts such as Cu-SSZ-13 and Cu-SAPO-34 with wide temperature windows and stable structure are considered and applied as commercial catalysts for NO_(x)removal in diesel vehicles for a long time.Although molecular sieve catalysts possess many advantages,they still cannot avoid the serious deactivation caused by various factors in practical applications.In this review,reasons leading to the deactivation of molecular sieve catalysts for NO_(x)reduction in actual working conditions were concluded.The deactivation mechanisms of molecular sieve catalysts for NO_(x)reduction were analyzed and the corresponding anti-deactivation strategies were summarized.Finally,challenges and prospects of molecular sieve catalysts for NO_(x)reduction were also proposed.
基金Supported by the National Natural Science Foundation of China(61503384,61603393)Natural Science Foundation of Jiangsu(BK20150199,BK20160275)+1 种基金the Foundation Research Funds for the Central Universities(2015QNA65)the Postdoctoral Foundation of Jiangsu Province(1501081B)
文摘Although industrial processes often perform perfectly under design conditions, they may deviate from the optimal operating point owing to parameters drift, environmental disturbances, etc. Thus, it is necessary to develop efficacious strategies or procedure to assess the process performance online. In this paper, we explore the issue of operating optimality assessment for complex industrial processes based on performance-similarity considering nonlinearities and outliers simultaneously, and a general enforced online performance assessment framework is proposed. In the offline part, a new and modified total robust kernel projection to latent structures algorithm,T-KPRM, is proposed and used to evaluate the complex nonlinear industrial process, which can effectively extract the optimal-index-related process variation information from process data and establish assessment models for each performance grades overcoming the effects of outlier. In the online part, the online assessment results can be obtained by calculating the similarity between the online data from a sliding window and each of the performance grades. Furthermore, in order to improve the accuracy of online assessment, we propose an online assessment strategy taking account of the effects of noise and process uncertainties. The Euclidean distance between the sliding data window and the optimal evaluation level is employed to measure the contribution rates of variables, which indicate the possible reason for the non-optimal operating performance. The proposed framework is tested on a real industrial case: dense medium coal preparation process, and the results shows the efficiency of the proposed method comparing to the existing method.
文摘Objective:To investigate the effect of Chinese massage combined with warm acupuncture on knee osteoarthritis.Methods:60 patients with knee osteoarthritis who were treated in our hospital from January 2017 to October 2019 were selected as the research subjects,and they were randomly divided into 2 groups of 30 patients each.The control group was treated with oral western medicine,and the observation group was treated with massage combined with warm acupuncture.The clinical efficacy and WOMAC index were compared between the two groups.Results:The total effective rate of the observation group was higher than that of the control group,and the WOMAC score was lower than that of the control group.The difference was statistically significant(P<0.05).Conclusion:Chinese massage combined with warm acupuncture is effective in treating knee osteoarthritis It can effectively alleviate the symptoms of pain and joint stiffness in patients,and improve joint mobility,which is worth for clinical promotion.
基金This work is financially supported by National Natural Science Foundation of China(52174283 and 52274308)Innovation Fund Project for Graduate Student of China University of Petroleum(East China)(22CX04023A)the Fundamental Research Funds for the Central Universities。
文摘The formation of multiple oxygen intermediates supporting efficient oxygen evolution reaction(OER)are affinitive with hydroxyl adsorption.However,ability of the catalyst to capture hydroxyl and maintain the continuous supply at active sits remains a tremendous challenge.Herein,an affordable Ni2P/FeP2 heterostructure is presented to form the internal polarization field(IPF),arising hydroxyl spillover(HOSo)during OER.Facilitated by IPF,the oriented HOSo from FeP2 to Ni2P can activate the Ni site with a new hydroxyl transmission channel and build the optimized reaction path of oxygen intermediates for lower adsorption energy,boosting the OER activity(242 mV vs.RHE at 100 mA cm-2)for least 100 h.More interestingly,for the anion exchange membrane water electrolyzer(AEMWE)with low concentration electrolyte,the advantage of HOSo effect is significantly amplified,delivering 1 A cm^(-2)at a low cell voltage of 1.88 V with excellent stability for over 50 h.
文摘Although reinforcement learning(RL)has shown great potential in industrial process coordinated optimization,its direct application to complex scheduling tasks such as the thickening-dewatering process is still limited by challenges including low sample efficiency and slow convergence.In this work,we propose an expert-augmented dual-stage reinforcement learning(EADS-RL)framework.In the first stage,expert data extracted from real industrial operation logs are used to pre-train both the policy and critic networks via imitation learning(IL),aiming to provide the agent with a reliable initial policy and thus accelerate the learning process.In the subsequent online RL optimization stage,EADS-RL effectively integrates expert priors and high-quality online experiences through a non-parametric regression model and a dynamic expert memory.The former offers reliable behavioral guidance for the agent to explore unknown state spaces,thereby improving exploration efficiency;the latter enables the expert memory to evolve by incorporating excellent trajectories discovered by the agent itself,facilitating continuous self-improvement of the policy.The simulation results demonstrate that EADS-RL significantly outperforms existing benchmark algorithms in terms of both convergence speed and final performance.In scheduling task evaluations,the proposed method not only achieves the lowest energy consumption but also attains the highest key process indicator(underflow concentration),while ensuring safe and stable process operation.These results highlight the substantial potential of EADS-RL for practical industrial applications.
基金supported by the National Natural Science Foundation of China(10971179)the Natural Science Foundation of Changzhou University(JS201008)
文摘The existence and multiplicity of positive solutions to a periodic boundary value problem for nonlinear third-order ordinary differential equation are established,based on the zero point theorem concerning cone expansion and compression of order type.Our main approach is different from the previous papers on the existence of multiple positive solutions to the similar problem.
文摘It gives us great pleasure to announce the launch of the Journal of Control and Decision(JCD).The primary aim of the journal is to provide a platform for scientists,engineers and practitioners throughout the world to present the latest advancement in Control,Decision,Automation,Robotics and Emerging Technologies.The journal publishes original contributions in both theory and applications,comprehensive technical reviews,survey papers and book reviews in all the areas of these disciplines.JCD is published quarterly by Taylor&Francis Group,UK.It has a strong editorial board team consisting of well-established researchers with vast professional experiences in various areas of the journal.All submitted papers will be reviewed on a peer review basis and handled by the editorial board of the journal.Only high-quality papers will be accepted for publication.
