With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivo...With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivotal for ensuring production safety,a critical factor in monitoring the health status of manufacturing apparatus.Conventional defect detection techniques,typically limited to specific scenarios,often require manual feature extraction,leading to inefficiencies and limited versatility in the overall process.Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes.Our proposed approach encompasses a suite of components:the high-level feature learning block(HLFLB),the multi-scale feature learning block(MSFLB),and a dynamic adaptive fusion block(DAFB),working in tandem to extract meticulously and synergistically aggregate defect-related characteristics across various scales and hierarchical levels.We have conducted validation of the proposed method using datasets derived from gearbox and bearing assessments.The empirical outcomes underscore the superior defect detection capability of our approach.It demonstrates consistently high performance across diverse datasets and possesses the accuracy required to categorize defects,taking into account their specific locations and the extent of damage,proving the method’s effectiveness and reliability in identifying defects in industrial components.展开更多
Climate clubs are valuable platforms for international and public-private collaboration in global climate governance;however,not all climate clubs enjoy durable support from their members.The existing literature attri...Climate clubs are valuable platforms for international and public-private collaboration in global climate governance;however,not all climate clubs enjoy durable support from their members.The existing literature attributes the varied fates of climate clubs to factors like legitimacy and club goods.We further argue that the norm-making function of clubs,the perceived value of club goods,and the costs of club good production collectively affect club development.We present a comparative study on two U.S.-initiated climate clubs-the Asia-Pacific Partnership on Clean Development and Climate(APP)and the Clean Energy Ministerial(CEM).While legitimacy concerns had some marginal influence on both clubs,the niche clubs occupy and the costs of club goods provision were crucial factors that influenced the two clubs’different fates.The APP’s failure was due to its focus on norm-making and providing information-oriented assistance to the private sector.As government interest in norm-making declined,the APP’s value declined accordingly.Moreover,assistance to private sector actors was costly and less attractive to governments.In comparison,the CEM found its niche by focusing on facilitating policymaking in the clean energy sector in a cost-efficient manner.To make clubs durable,constructing an action-oriented working environment and providing value-added and low-cost services to key stakeholders are of great importance.展开更多
Wastewater treatment is an important source of greenhouse gases(GHGs).Yet large uncertainties remain in the quantification of GHG emissions from municipal wastewater treatment plants(MWWTPs)in China.A high-resolution ...Wastewater treatment is an important source of greenhouse gases(GHGs).Yet large uncertainties remain in the quantification of GHG emissions from municipal wastewater treatment plants(MWWTPs)in China.A high-resolution and technology-specific emission inventory is still lacking to support mitigation strategies of MWWTPs.Here we develop a plant-level and technology-based MWWTP emission inventory for China covering 8703 plants and 19 treatment technology categories by compiling and harmonizing the most up-to-date facility-level databases.China's methane(CH_(4))and nitrous oxide(N_(2)O)emissions from MWWTPs in 2020 are estimated to be 150.6 Gg and 22.0 Gg,respectively,with the uncertainty range of-30%to 37%and-30%to 26%at 95%confidence interval.We find an emission inequality across cities,with the richest cities emitting two times more CH_(4)and N_(2)O per capita from municipal wastewater treatment than the poorest cities.The emitted CH_(4)and N_(2)O are dominated by Anaerobic/Anoxic/Oxic-,Sequencing Batch Reactor-,Oxidation Ditch-,and Anoxic/Oxic-based MWWTPs of less than 20 years old.Considering the relatively young age structure of China's MWWTPs,the committed emissions highlight the importance of reducing on-site GHG emissions by optimization of operating conditions and innovation management.The emission differences among our estimates,previous studies,and the Intergovernmental Panel on Climate Change guidelines are largely attributed to the uncertainties in emission factors,implying the urgent need for more plant-integrated measurements to improve the accuracy of emission accounting.展开更多
To achieve excellent electromagnetic wave(EMW)absorption properties,the microstructure design of the absorber is critical.In this work,six kinds of N-Ni/C nanostructures with different morphologies were prepared by on...To achieve excellent electromagnetic wave(EMW)absorption properties,the microstructure design of the absorber is critical.In this work,six kinds of N-Ni/C nanostructures with different morphologies were prepared by one-step hydrothermal method and high temperature carbonization by adjusting the types of nickel salts and reaction solvents.The EMW absorption performance of six different morphologies of N-Ni/C nanostructures was compared and analyzed.Among them,it is found that the nanoflowerlike N-Ni/C composite has excellent dielectric loss and magnetic loss synergistic effect due to its polycrystalline structure,and can obtain excellent EMW absorption performance.The minimum reflection loss value at a thickness of 1.9 mm is-59.56 dB at 16.88 GHz,and the effective absorption bandwidth value reaches 6.0 GHz at a thickness of 2.2 mm.Our research shows that different morphologies and multiple lattice structures of nanostructures with the same composition have a significant influence on EMW absorption performance,which provides new research ideas for developing high-performance EMW absorbing materials.展开更多
Various phototheranostics have recently been developed for phototherapy.Through proper molecular design,the photochemical and photophysical properties of these phototheranostics can be promoted.Herein,an acceptor-dono...Various phototheranostics have recently been developed for phototherapy.Through proper molecular design,the photochemical and photophysical properties of these phototheranostics can be promoted.Herein,an acceptor-donor-acceptor(A-D-A)-structured dye,BTP-4F-DMO,was synthesized and prepared into water-soluble nanoparticles(NPs).The obtained BTP-4F-DMO NPs had strong absorption from650 nm to 850 nm and a fluorescence emission peak at~900 nm that tailed to~1100 nm.The NPs showed a superhigh photothermal conversion efficiency of 90.5%±5%and could simultaneously generate·OH and^(1)O_(2)with a^(1)O_(2)generation quantum yield of 4.6%under 808 nm laser irradiation.Due to these advanced properties,BTP-4F-DMO NPs can switch the role of autophagy from pro-survival to prodeath,thereby further promoting cancer cell death.These features make BTP-4F-DMO NPs a promising multifunctional phototheranostic agent for NIR-II fluorescence/photoacoustic dual-mode imaging-guided synergetic photodynamic/photothermal therapy.In general,this work provides a strategy for expanding the biomedical applications of organic A-D-A-structured phototheranostics.展开更多
The development of global information technology makes human life intelligent,and the large-scale use of various electronic devices increases the electromagnetic radiation in the surrounding environment.This has creat...The development of global information technology makes human life intelligent,and the large-scale use of various electronic devices increases the electromagnetic radiation in the surrounding environment.This has created a requirement for the development of high-performance electromagnetic wave absorbers to eliminate electromagnetic pollution.However,the preparation of electromagnetic wave absorbers with excellent electromagnetic loss capability remains a great challenge.Here,we present a method to prepare Co/ZnO/C@MWCNTs(CZC@M)composites by pyrolysis of ZnCo-MOF@MWCNTs(MOF@M).Specifically,MWCNTs are uniformly distributed on the CZC surface to form multiple heterogeneous interfaces,which will lead to an increase in polarizability.In addition,changing the amounts of MWCNTs in the composite can modulate its dielectric constant and impedance matching properties.Impressively,at only 10%sample content,the minimum reflection loss of-41.75 d B and the maximum effective absorption bandwidth of 4.72 GHz are obtained at thicknesses of 2.4 mm and 2.2 mm,respectively.Overall,the results reported in this work provide a new design strategy for the synthesis of high-performance electromagnetic wave absorbers with potential applications in the elimination of electromagnetic pollution.展开更多
This paper presents a winning solution for the CCKS-2020 financial event extraction task, where the goal is to identify event types, triggers and arguments in sentences across multiple event types. In this task, we fo...This paper presents a winning solution for the CCKS-2020 financial event extraction task, where the goal is to identify event types, triggers and arguments in sentences across multiple event types. In this task, we focus on resolving two challenging problems(i.e., low resources and element overlapping) by proposing a joint learning framework, named SaltyFishes. We first formulate the event extraction task as a joint probability model. By sharing parameters in the model across different types, we can learn to adapt to low-resource events based on high-resource events. We further address the element overlapping problems by a mechanism of Conditional Layer Normalization, achieving even better extraction accuracy. The overall approach achieves an F1-score of 87.8% which ranks the first place in the competition.展开更多
In recent years,Apache Spark has become the de facto standard for big data processing.SparkSQL is a module offering support for relational analysis on Spark with Structured Query Language(SQL).SparkSQL provides conven...In recent years,Apache Spark has become the de facto standard for big data processing.SparkSQL is a module offering support for relational analysis on Spark with Structured Query Language(SQL).SparkSQL provides convenient data processing interfaces.Despite its efficient optimizer,SparkSQL still suffers from the inefficiency of Spark resulting from Java virtual machine and the unnecessary data serialization and deserialization.Adopting native languages such as C++could help to avoid such bottlenecks.Benefiting from a bare-metal runtime environment and template usage,systems with C++interfaces usually achieve superior performance.However,the complexity of native languages also increases the required programming and debugging efforts.In this work,we present LotusSQL,an engine to provide SQL support for dataset abstraction on a native backend Lotus.We employ a convenient SQL processing framework to deal with frontend jobs.Advanced query optimization technologies are added to improve the quality of execution plans.Above the storage design and user interface of the compute engine,LotusSQL implements a set of structured dataset operations with high efficiency and integrates them with the frontend.Evaluation results show that LotusSQL achieves a speedup of up to 9 in certain queries and outperforms Spark SQL in a standard query benchmark by more than 2 on average.展开更多
基金supported by the Natural Science Foundation of Heilongjiang Province(Grant Number:LH2021F002).
文摘With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivotal for ensuring production safety,a critical factor in monitoring the health status of manufacturing apparatus.Conventional defect detection techniques,typically limited to specific scenarios,often require manual feature extraction,leading to inefficiencies and limited versatility in the overall process.Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes.Our proposed approach encompasses a suite of components:the high-level feature learning block(HLFLB),the multi-scale feature learning block(MSFLB),and a dynamic adaptive fusion block(DAFB),working in tandem to extract meticulously and synergistically aggregate defect-related characteristics across various scales and hierarchical levels.We have conducted validation of the proposed method using datasets derived from gearbox and bearing assessments.The empirical outcomes underscore the superior defect detection capability of our approach.It demonstrates consistently high performance across diverse datasets and possesses the accuracy required to categorize defects,taking into account their specific locations and the extent of damage,proving the method’s effectiveness and reliability in identifying defects in industrial components.
基金We acknowledge financial support from Shanghai Pujiang Program[Grant number.2020PJC010]the Social Science and Humanities Research Council of Canada.
文摘Climate clubs are valuable platforms for international and public-private collaboration in global climate governance;however,not all climate clubs enjoy durable support from their members.The existing literature attributes the varied fates of climate clubs to factors like legitimacy and club goods.We further argue that the norm-making function of clubs,the perceived value of club goods,and the costs of club good production collectively affect club development.We present a comparative study on two U.S.-initiated climate clubs-the Asia-Pacific Partnership on Clean Development and Climate(APP)and the Clean Energy Ministerial(CEM).While legitimacy concerns had some marginal influence on both clubs,the niche clubs occupy and the costs of club goods provision were crucial factors that influenced the two clubs’different fates.The APP’s failure was due to its focus on norm-making and providing information-oriented assistance to the private sector.As government interest in norm-making declined,the APP’s value declined accordingly.Moreover,assistance to private sector actors was costly and less attractive to governments.In comparison,the CEM found its niche by focusing on facilitating policymaking in the clean energy sector in a cost-efficient manner.To make clubs durable,constructing an action-oriented working environment and providing value-added and low-cost services to key stakeholders are of great importance.
基金supported by the Shenzhen Science and Technology Innovation Commission(No.RCBS20210609103731062,No.WDZC20220810110301001)Guangdong Basic and Applied Basic Research Foundation(No.2021A1515110887)H.L.acknowledge additional support from the Shenzhen Overseas High-Level Talent Project.
文摘Wastewater treatment is an important source of greenhouse gases(GHGs).Yet large uncertainties remain in the quantification of GHG emissions from municipal wastewater treatment plants(MWWTPs)in China.A high-resolution and technology-specific emission inventory is still lacking to support mitigation strategies of MWWTPs.Here we develop a plant-level and technology-based MWWTP emission inventory for China covering 8703 plants and 19 treatment technology categories by compiling and harmonizing the most up-to-date facility-level databases.China's methane(CH_(4))and nitrous oxide(N_(2)O)emissions from MWWTPs in 2020 are estimated to be 150.6 Gg and 22.0 Gg,respectively,with the uncertainty range of-30%to 37%and-30%to 26%at 95%confidence interval.We find an emission inequality across cities,with the richest cities emitting two times more CH_(4)and N_(2)O per capita from municipal wastewater treatment than the poorest cities.The emitted CH_(4)and N_(2)O are dominated by Anaerobic/Anoxic/Oxic-,Sequencing Batch Reactor-,Oxidation Ditch-,and Anoxic/Oxic-based MWWTPs of less than 20 years old.Considering the relatively young age structure of China's MWWTPs,the committed emissions highlight the importance of reducing on-site GHG emissions by optimization of operating conditions and innovation management.The emission differences among our estimates,previous studies,and the Intergovernmental Panel on Climate Change guidelines are largely attributed to the uncertainties in emission factors,implying the urgent need for more plant-integrated measurements to improve the accuracy of emission accounting.
基金This work was financially supported by the National Natural Science Foundation of China(Nos.51407134 and 52002196)the Natural Science Foundation of Shandong Province(Nos.ZR2019YQ24 and ZR2020QF084)+2 种基金the Taishan Scholars and Young Experts Program of Shandong Province(No.tsqn202103057)the Qingchuang Talents Induction Program of Shandong Higher Education Institution(Research and Innovation Team of Structural-Functional Polymer Composites)the Special Financial of Shandong Province(Structural Design of High-efficiency Electromagnetic Wave-absorbing Composite Materials and Construction of Shandong Provincial Talent Teams(No.37000022P990304116449)).
文摘To achieve excellent electromagnetic wave(EMW)absorption properties,the microstructure design of the absorber is critical.In this work,six kinds of N-Ni/C nanostructures with different morphologies were prepared by one-step hydrothermal method and high temperature carbonization by adjusting the types of nickel salts and reaction solvents.The EMW absorption performance of six different morphologies of N-Ni/C nanostructures was compared and analyzed.Among them,it is found that the nanoflowerlike N-Ni/C composite has excellent dielectric loss and magnetic loss synergistic effect due to its polycrystalline structure,and can obtain excellent EMW absorption performance.The minimum reflection loss value at a thickness of 1.9 mm is-59.56 dB at 16.88 GHz,and the effective absorption bandwidth value reaches 6.0 GHz at a thickness of 2.2 mm.Our research shows that different morphologies and multiple lattice structures of nanostructures with the same composition have a significant influence on EMW absorption performance,which provides new research ideas for developing high-performance EMW absorbing materials.
基金supported by the National Natural Science Foundation of China(Nos.61805287 and 62175262)the Innovation-Driven Project of Central South University(No.2020CX021)。
文摘Various phototheranostics have recently been developed for phototherapy.Through proper molecular design,the photochemical and photophysical properties of these phototheranostics can be promoted.Herein,an acceptor-donor-acceptor(A-D-A)-structured dye,BTP-4F-DMO,was synthesized and prepared into water-soluble nanoparticles(NPs).The obtained BTP-4F-DMO NPs had strong absorption from650 nm to 850 nm and a fluorescence emission peak at~900 nm that tailed to~1100 nm.The NPs showed a superhigh photothermal conversion efficiency of 90.5%±5%and could simultaneously generate·OH and^(1)O_(2)with a^(1)O_(2)generation quantum yield of 4.6%under 808 nm laser irradiation.Due to these advanced properties,BTP-4F-DMO NPs can switch the role of autophagy from pro-survival to prodeath,thereby further promoting cancer cell death.These features make BTP-4F-DMO NPs a promising multifunctional phototheranostic agent for NIR-II fluorescence/photoacoustic dual-mode imaging-guided synergetic photodynamic/photothermal therapy.In general,this work provides a strategy for expanding the biomedical applications of organic A-D-A-structured phototheranostics.
基金the Natural Science Foundation of Shandong Province(No.ZR2019YQ24)Taishan Scholars and Young Experts Program of Shandong Province(No.tsqn202103057)the Qingchuang Talents Induction Program of Shandong Higher Education Institution(Research and Innovation Team of Structural-Functional Polymer Composites)。
文摘The development of global information technology makes human life intelligent,and the large-scale use of various electronic devices increases the electromagnetic radiation in the surrounding environment.This has created a requirement for the development of high-performance electromagnetic wave absorbers to eliminate electromagnetic pollution.However,the preparation of electromagnetic wave absorbers with excellent electromagnetic loss capability remains a great challenge.Here,we present a method to prepare Co/ZnO/C@MWCNTs(CZC@M)composites by pyrolysis of ZnCo-MOF@MWCNTs(MOF@M).Specifically,MWCNTs are uniformly distributed on the CZC surface to form multiple heterogeneous interfaces,which will lead to an increase in polarizability.In addition,changing the amounts of MWCNTs in the composite can modulate its dielectric constant and impedance matching properties.Impressively,at only 10%sample content,the minimum reflection loss of-41.75 d B and the maximum effective absorption bandwidth of 4.72 GHz are obtained at thicknesses of 2.4 mm and 2.2 mm,respectively.Overall,the results reported in this work provide a new design strategy for the synthesis of high-performance electromagnetic wave absorbers with potential applications in the elimination of electromagnetic pollution.
基金This work is supported by the National Key Research and Development Program of China(No.2016YFB1000105)the National Natural Science Foundation of China(No.61772151)+1 种基金This work’s computing device is also supported by Beijing Advanced Innovation Center of Big Data and Brain Computing,Beihang UniversityThe author Shu Guo is supported by“Zhizi Program”.
文摘This paper presents a winning solution for the CCKS-2020 financial event extraction task, where the goal is to identify event types, triggers and arguments in sentences across multiple event types. In this task, we focus on resolving two challenging problems(i.e., low resources and element overlapping) by proposing a joint learning framework, named SaltyFishes. We first formulate the event extraction task as a joint probability model. By sharing parameters in the model across different types, we can learn to adapt to low-resource events based on high-resource events. We further address the element overlapping problems by a mechanism of Conditional Layer Normalization, achieving even better extraction accuracy. The overall approach achieves an F1-score of 87.8% which ranks the first place in the competition.
文摘In recent years,Apache Spark has become the de facto standard for big data processing.SparkSQL is a module offering support for relational analysis on Spark with Structured Query Language(SQL).SparkSQL provides convenient data processing interfaces.Despite its efficient optimizer,SparkSQL still suffers from the inefficiency of Spark resulting from Java virtual machine and the unnecessary data serialization and deserialization.Adopting native languages such as C++could help to avoid such bottlenecks.Benefiting from a bare-metal runtime environment and template usage,systems with C++interfaces usually achieve superior performance.However,the complexity of native languages also increases the required programming and debugging efforts.In this work,we present LotusSQL,an engine to provide SQL support for dataset abstraction on a native backend Lotus.We employ a convenient SQL processing framework to deal with frontend jobs.Advanced query optimization technologies are added to improve the quality of execution plans.Above the storage design and user interface of the compute engine,LotusSQL implements a set of structured dataset operations with high efficiency and integrates them with the frontend.Evaluation results show that LotusSQL achieves a speedup of up to 9 in certain queries and outperforms Spark SQL in a standard query benchmark by more than 2 on average.
