Photothermoelectric(PTE)photodetectors with selfpowered and uncooled advantages have attracted much interest due to the wide application prospects in the military and civilian fields.However,traditional PTE photodetec...Photothermoelectric(PTE)photodetectors with selfpowered and uncooled advantages have attracted much interest due to the wide application prospects in the military and civilian fields.However,traditional PTE photodetectors lack of mechanical flexibility and cannot operate independently without the test instrument.Herein,we present a flexible PTE photodetector capable of dual-mode output,combining electrical and optical signal generation for enhanced functionality.Using solution processing,high-quality MXene thin films are assembled on asymmetric electrodes as the photosensitive layer.The geometrically asymmetric electrode design significantly enhances the responsivity,achieving 0.33 m A W^(-1)under infrared illumination,twice that of the symmetrical configuration.This improvement stems from optimized photothermal conversion and an expanded temperature gradient.The PTE device maintains stable performance after 300 bending cycles,demonstrating excellent flexibility.A new energy conversion pathway has been established by coupling the photothermal conversion of MXene with thermochromic composite materials,leading to a real-time visualization of invisible infrared radiation.Leveraging this functionality,we demonstrate the first human-machine collaborative infrared imaging system,wherein the dual-mode photodetector arrays synchronously generate human-readable pattern and machine-readable pattern.Our study not only provides a new solution for functional integration of flexible photodetectors,but also sets a new benchmark for human-machine collaborative optoelectronics.展开更多
In the parallel steering coordination control strategy for path tracking,it is difficult to match the current driver steering model using the fixed parameters with the actual driver,and the designed steering coordinat...In the parallel steering coordination control strategy for path tracking,it is difficult to match the current driver steering model using the fixed parameters with the actual driver,and the designed steering coordination control strategy under a single objective and simple conditions is difficult to adapt to the multi-dimensional state variables’input.In this paper,we propose a deep reinforcement learning algorithm-based multi-objective parallel human-machine steering coordination strategy for path tracking considering driver misoperation and external disturbance.Firstly,the driver steering mathematical model is constructed based on the driver preview characteristics and steering delay response,and the driver characteristic parameters are fitted after collecting the actual driver driving data.Secondly,considering that the vehicle is susceptible to the influence of external disturbances during the driving process,the Tube MPC(Tube Model Predictive Control)based path tracking steering controller is designed based on the vehicle system dynamics error model.After verifying that the driver steering model meets the driver steering operation characteristics,DQN(Deep Q-network),DDPG(Deep Deterministic Policy Gradient)and TD3(Twin Delayed Deep Deterministic Policy Gradient)deep reinforcement learning algorithms are utilized to design a multi-objective parallel steering coordination strategy which satisfies the multi-dimensional state variables’input of the vehicle.Finally,the tracking accuracy,lateral safety,human-machine conflict and driver steering load evaluation index are designed in different driver operation states and different road environments,and the performance of the parallel steering coordination control strategies with different deep reinforcement learning algorithms and fuzzy algorithms are compared by simulations and hardware in the loop experiments.The results show that the parallel steering collaborative strategy based on a deep reinforcement learning algorithm can more effectively assist the driver in tracking the target path under lateral wind interference and driver misoperation,and the TD3-based coordination control strategy has better overall performance.展开更多
Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results ca...Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.展开更多
Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may r...Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships.Networking structures are highly sensitive in social networks,requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks.In addition,they miss out on accurately identifying clusters.Since single-objective optimization cannot always generate accurate and comprehensive results,as multi-objective optimization can.Therefore,we utilized two objective functions that enable strong connections between communities and weak connections between them.In this study,we utilized the intra function,which has proven effective in state-of-the-art research studies.We proposed a new inter-function that has demonstrated its effectiveness by making the objective of detecting external connections between communities is to make them more distinct and sparse.Furthermore,we proposed a Multi-Objective community strength enhancement algorithm(MOCSE).The proposed algorithm is based on the framework of the Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),integrated with a new heuristic mutation strategy,community strength enhancement(CSE).The results demonstrate that the model is effective in accurately identifying community structures while also being computationally efficient.The performance measures used to evaluate the MOEA/D algorithm in our work are normalized mutual information(NMI)and modularity(Q).It was tested using five state-of-the-art algorithms on social networks,comprising real datasets(Zachary,Dolphin,Football,Krebs,SFI,Jazz,and Netscience),as well as twenty synthetic datasets.These results provide the robustness and practical value of the proposed algorithm in multi-objective community identification.展开更多
Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community asse...Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community assembly in virgin and aging MP plastispheres across different habitats is poorly understood.This study aims to assess the variations in bacterial community assembly across different niches and habitats with an in situ ex-periment,in which constructed forest wetland(FW),natural lake wetland(LW),and lotus pond wetland(LP)were habitats,and plastispheres of virgin and aging low-density polyethylene(LDPE)MPs,as well as surround-ing wetland soils were niches.Significant niche-related differences in bacterial communities were observed,with lower diversity and enrichment of potential plastic-degrading bacteria in the plastisphere than in the soil bacterial communities.Furthermore,habitat-related differences exerted a more pronounced influence on the beta-diversity patterns of the bacterial communities.The linear regression analyses indicated that the local species pool con-tributed more to bacterial community assembly in the LW wetland,whereas the relative abundance of species was the primary factor in the LP wetland.The null model analysis indicated that plastisphere bacterial communi-ties were predominantly driven by the stochastic process,with a more deterministic assembly observed in the LP wetland and soil bacterial communities.Additionally,the primary ecological process shaping plastisphere com-munities shifted from drift in the virgin LDPE to homogenising dispersal in the aging LDPE.This study provides new insights into the fate and ecological impacts of MPs in wetlands,thereby facilitating the effective regulations of plastic pollution.展开更多
Fungi play crucial roles in nutrient acquisition,plant growth promotion,and the enhancement of resistance to both abiotic and biotic stresses.However,studies on the fungal communities associated with peas (Pisum sativ...Fungi play crucial roles in nutrient acquisition,plant growth promotion,and the enhancement of resistance to both abiotic and biotic stresses.However,studies on the fungal communities associated with peas (Pisum sativum L.) remain limited.In this study,we systematically investigated the ecological effects of host niches (soil,root,stem,leaf,and pod) and genotypes on the diversity and composition of fungal communities in peas using a multi-level approach that encompassed pattern recognition (β-diversity decomposition),mechanism validation (neutral community model testing),and dynamic tracking methods (migration pathway source-tracking).The results revealed that the dominant fungal phyla across niches and genotypes were Ascomycota,Basidiomycota,and Mortierellomycota,and the community structures of the soil–plant continuum were primarily determined by the pea niches rather than genotypes.β-diversity decomposition was largely attributed to species replacement rather than richness differences,indicating strong niche specificity and microbial replacement across microhabitats.Neutral model analysis revealed that stochastic processes influenced genotypeassociated communities,while deterministic processes played a dominant role in niche-based community assembly.Source-tracking analysis identified niche-to-niche fungal migration,with Erysiphe,Fusarium,Cephaliophora,Ascobolus,Alternaria,and Aspergillus as the key genera.Migration rates from exogenous to endogenous niches were low (1.3–61.5%),whereas those within exogenous (64.4–83.7%) or endogenous (73.9–96.4%) compartments were much higher,suggesting that the pea epidermis acts as a selective barrier that filters and enriches microbial communities prior to internal colonization.This study provides comprehensive insights into the mechanisms of host filtering,enrichment and microbial sourcing,which increases our understanding of the assembly rules of the pea-associated fungal microbiome.展开更多
Professional learning communities(PLCs)offer essential contextual support for the development of foreign language teachers in higher education.The book Building Professional Learning Communities of Foreign Language Te...Professional learning communities(PLCs)offer essential contextual support for the development of foreign language teachers in higher education.The book Building Professional Learning Communities of Foreign Language Teachers in Higher Education,co-authored by Wen et al.(2021)systematically examines the necessity,practical measures,theoretical construction,and outcomes associated with building PLCs for university foreign language teachers.Notably,it introduces a research methodology rooted in local teacher education practices with Chinese characteristics—the dialectical research paradigm(DRP).This review introduces the content of the book,evaluates its contributions to teacher development,and explores its implications for future practice and research.展开更多
Prolonged droughts have emerged as a major impediment to the revitalization of pastoral regions worldwide because they significantly augment their susceptibility to the deleterious effects of global climate change,ove...Prolonged droughts have emerged as a major impediment to the revitalization of pastoral regions worldwide because they significantly augment their susceptibility to the deleterious effects of global climate change,overgrazing,and land degradation.This study,conducted in 106 pastoral villages across 33 pastoral banners of Inner Mongolia Autonomous Region of China between August 2021 and October 2022,used a community resilience evaluation indicator system to assess drought resistance.By calculating a community resilience index,the research explored influencing factors and proposed countermeasures,aiming to enhance resilience to prolonged drought.The results revealed three key findings.1)Pastoral areas exhibited a limited degree of community resilience to drought disasters(overall score=0.28),with resilience levels forming a pyramid-shaped hierarchy.2)Dimensional analysis showed that resilience scores decreased sequentially across five domains:social(0.53)>cultural(0.44)>environmental(0.38)>economic(0.32)>management(0.27).These results highlight the crucial role of economic and management resilience in enhancing community resilience,particularly when accompanied by pre-and post-disaster government support and social security,both of which must be improved.3)Key factors influencing community resilience included geographical location,traffic accessibility,and frequency and severity of droughts.From a drought resilience perspective,targeted strategies and recommendations are proposed to provide novel and practical approaches for achieving sustainable development in pastoral areas and rural regions as a whole.展开更多
In this work,ofloxacin(OFL),a kind of frequently detected antibiotic in groundwater,was selected to explore its impact(at ng/L-μg/L-level)on denitrification performance in an autotrophic denitrification system driven...In this work,ofloxacin(OFL),a kind of frequently detected antibiotic in groundwater,was selected to explore its impact(at ng/L-μg/L-level)on denitrification performance in an autotrophic denitrification system driven by pyrite/sulfur(FeS2/S0).Results showed that OFL restrained nitrate removal efficiency,and the inhibition degree was positively related to the concentration of OFL.After being exposed to increased OFL(200 ng/L-100μg/L)for 69 days,higher inhibition of electron transport activity(ETSA),enzyme activities of nitrate reductase(NAR),and nitrite reductase(NIR)were acquired.Meanwhile,the extracellular protein(PN)content of sludge samples was remarkably stimulated by OFL to resist the augmented toxicity.OFL contributed to increased microbial diversity and sulfur/sulfide oxidation functional genes in ng/L-level bioreactors,whereas led to a decline inμg/L level experiments.With OFL at concentrations of 200 ng/L and 100μg/L,the whole expression of 10 key denitrification functional genes was depressed,and the higher the OFL concentration,the lower the expression level.However,no significant proliferation of antibiotic resistance genes(ARGs)either in 200 ng/L-OFL or 100μg/L-OFL groups was observed.Two-factor correlation analysis results indicated that Thiobacillus,Anaerolineae,Anaerolineales,and Nitrospirae might be the main hosts of existing ARGs in this system.展开更多
As a Burundian doctoral student at Nanjing University,my personal journey is closely intertwined with China’s development in the new era and the deepening China-Africa partnership.Recently,my experiences have given m...As a Burundian doctoral student at Nanjing University,my personal journey is closely intertwined with China’s development in the new era and the deepening China-Africa partnership.Recently,my experiences have given me a deeper appreciation of the importance of people-to-people exchanges between China and Africa.展开更多
In the countryside of east Zhejiang Province,a quiet village has hit a home run.Xujiadai,once a place known for pig farming and environmental pollution,is drawing visitors from across China with a sport still uncommon...In the countryside of east Zhejiang Province,a quiet village has hit a home run.Xujiadai,once a place known for pig farming and environmental pollution,is drawing visitors from across China with a sport still uncommon in the country:baseball.展开更多
In 2021,approximately 537 million people suffered from diabetes mellitus(DM)globally,and this figure will increase to approximately 783 million within the next quarter-century.The increasing burden of DM is a pressing...In 2021,approximately 537 million people suffered from diabetes mellitus(DM)globally,and this figure will increase to approximately 783 million within the next quarter-century.The increasing burden of DM is a pressing global public health issue.Therefore,the early identification of high-risk groups and implementation of effective intervention measures is imperative.展开更多
Urinary tract infections(UTIs)are among the most prevalent pediatric bacterial infections,and undertreated episodes may lead to renal scarring,hypertension,or chronic kidney disease.Multidrug-resistant(MDR)Enterobacte...Urinary tract infections(UTIs)are among the most prevalent pediatric bacterial infections,and undertreated episodes may lead to renal scarring,hypertension,or chronic kidney disease.Multidrug-resistant(MDR)Enterobacterales have been increasingly reported in children,with higher rates in Asian and Middle Eastern settings than in high-income countries[1,2].展开更多
Electromyography(EMG)has already been broadly used in human-machine interaction(HMI)applications.Determining how to decode the information inside EMG signals robustly and accurately is a key problem for which we urgen...Electromyography(EMG)has already been broadly used in human-machine interaction(HMI)applications.Determining how to decode the information inside EMG signals robustly and accurately is a key problem for which we urgently need a solution.Recently,many EMG pattern recognition tasks have been addressed using deep learning methods.In this paper,we analyze recent papers and present a literature review describing the role that deep learning plays in EMG-based HMI.An overview of typical network structures and processing schemes will be provided.Recent progress in typical tasks such as movement classification,joint angle prediction,and force/torque estimation will be introduced.New issues,including multimodal sensing,inter-subject/inter-session,and robustness toward disturbances will be discussed.We attempt to provide a comprehensive analysis of current research by discussing the advantages,challenges,and opportunities brought by deep learning.We hope that deep learning can aid in eliminating factors that hinder the development of EMG-based HMI systems.Furthermore,possible future directions will be presented to pave the way for future research.展开更多
Hydrogel-based triboelectric nanoge nerator(TENG)has a promising applied prospect in wearable electronic devices.However,its low performance,poor stability,insufficient recyclability and inferior self-healing seriousl...Hydrogel-based triboelectric nanoge nerator(TENG)has a promising applied prospect in wearable electronic devices.However,its low performance,poor stability,insufficient recyclability and inferior self-healing seriously hinder its development.Herein,we report a robust route to a liquid metal(LM)/polyvinyl alcohol(PVA)hydrogel-based TENG(LP-TENG).Owing to the intrinsically liquid feature of conductive LM within the flexible PVA hydrogel,the as-prepared LP-TENG exhibited comprehensiye advantages of adaptability,biocompatibility,outstanding electrical performance,superior stability,recyclability and diverse applications,which were unattainable by traditional systems.Concretely,the LP-TENG delivered appealing open circuit voltage of 250 V,short circuit current of 4μA and transferred charge of 120 nC with high stability,outperforming most advanced TENG systems.The LP-TENG was successfully employed for versatile applications with multifunctionality,including human motion detection,handwriting recognition,energy collection,message transmission and human-machine interaction.This work presents significant prospects for crafting advanced materials and devices in the fields of wearable electronics,flexible skin and smart robots.展开更多
Combination flexible and stretchable textiles with self-powered sensors bring a novel insight into wearable functional electronics and cyber security in the era of Internet of Things.This work presents a highly flexib...Combination flexible and stretchable textiles with self-powered sensors bring a novel insight into wearable functional electronics and cyber security in the era of Internet of Things.This work presents a highly flexible and self-powered fully fabric-based triboelectric nanogenerator(F-TENG)with sandwiched structure for biomechanical energy harvesting and real-time biometric authentication.The prepared F-TENG can power a digital watch by low-frequency motion and respond to the pressure change by the fall of leaves.A self-powered wearable keyboard(SPWK)is also fabricated by integrating large-area F-TENG sensor arrays,which not only can trace and record electrophysiological signals,but also can identify individuals’typing characteristics by means of the Haar wavelet.Based on these merits,the SPWK has promising applications in the realm of wearable electronics,self-powered sensors,cyber security,and artificial intelligences.展开更多
We outline problems and potential solutions for feasible human-machine interfaces using cable-based parallel manipulators for physiotherapy applications.From an engineering perspective,we discuss the design constraint...We outline problems and potential solutions for feasible human-machine interfaces using cable-based parallel manipulators for physiotherapy applications.From an engineering perspective,we discuss the design constraints related to acceptance by patients and physiotherapist users.To date,most designs have focused on mobile platforms that are designed to be operated as an end-effector connected to human limbs for direct patient interaction.Some specific examples are illustrated from the authors' experience with prototypes available at Laboratory of Robotics and Mechatronics (LARM),Italy.展开更多
To reduce the complexity of the configuration and control strategy for shoulder rehabilitation exoskeleton,a 2R1R1P2R serial of shoulder exoskeleton based on gravity balance is proposed.Based on three basic rotatory s...To reduce the complexity of the configuration and control strategy for shoulder rehabilitation exoskeleton,a 2R1R1P2R serial of shoulder exoskeleton based on gravity balance is proposed.Based on three basic rotatory shoulder joints,an exact kinematic constraint system can be formed between the exoskeleton and the upper arm by introducing a passive sliding pair and a center of glenohumeral(CGH)unpowered compensation mechanism,which realizes the human-machine kinematic compatibility.Gravity balance is used in the CGH compensation mechanism to provide shoulder joint support.Meanwhile,the motion of the compensation mechanism is pulled by doing reverse leading through the arm to realize the kinematic self-adaptive,which decreases control complexity.Besides,a simple and intuitive spring adjustment strategy is proposed to ensure the gravity balance of any prescribed quality.Furthermore,according to the influencing factors analysis of the scapulohumeral rhythm,the kinematic analysis of CGH mechanism is performed,which shows that the mechanism can fit the trajectory of CGH under various conditions.Finally,the dynamic simulation of the mechanism is carried out.Results indicate that the compensation torques are reduced to below 0.22 N·m,and the feasibility of the mechanism is also verified.展开更多
The Chinese express delivery industry processes nearly 110 billion items in 2022,averaging an annual growth rate of 200%.Among the various types of sorting systems used for handling express items,cross-belt sorting sy...The Chinese express delivery industry processes nearly 110 billion items in 2022,averaging an annual growth rate of 200%.Among the various types of sorting systems used for handling express items,cross-belt sorting systems stand out as the most crucial.However,despite their high degree of automation,the workload for operators has intensified owing to the surging volume of express items.In the era of Industry 5.0,it is imperative to adopt new technologies that not only enhance worker welfare but also improve the efficiency of cross-belt systems.Striking a balance between efficiency in handling express items and operator well-being is challenging.Digital twin technology offers a promising solution in this respect.A realization method of a human-machine integrated digital twin is proposed in this study,enabling the interaction of biological human bodies,virtual human bodies,virtual equipment,and logistics equipment in a closed loop,thus setting an operating framework.Key technologies in the proposed framework include a collection of heterogeneous data from multiple sources,construction of the relationship between operator fatigue and operation efficiency based on physiological measurements,virtual model construction,and an online optimization module based on real-time simulation.The feasibility of the proposed method was verified in an express distribution center.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(xxj022019009)。
文摘Photothermoelectric(PTE)photodetectors with selfpowered and uncooled advantages have attracted much interest due to the wide application prospects in the military and civilian fields.However,traditional PTE photodetectors lack of mechanical flexibility and cannot operate independently without the test instrument.Herein,we present a flexible PTE photodetector capable of dual-mode output,combining electrical and optical signal generation for enhanced functionality.Using solution processing,high-quality MXene thin films are assembled on asymmetric electrodes as the photosensitive layer.The geometrically asymmetric electrode design significantly enhances the responsivity,achieving 0.33 m A W^(-1)under infrared illumination,twice that of the symmetrical configuration.This improvement stems from optimized photothermal conversion and an expanded temperature gradient.The PTE device maintains stable performance after 300 bending cycles,demonstrating excellent flexibility.A new energy conversion pathway has been established by coupling the photothermal conversion of MXene with thermochromic composite materials,leading to a real-time visualization of invisible infrared radiation.Leveraging this functionality,we demonstrate the first human-machine collaborative infrared imaging system,wherein the dual-mode photodetector arrays synchronously generate human-readable pattern and machine-readable pattern.Our study not only provides a new solution for functional integration of flexible photodetectors,but also sets a new benchmark for human-machine collaborative optoelectronics.
基金Supported by National Natural Science Foundation of China(Grant Nos.U22A20246,52372382)Hefei Municipal Natural Science Foundation(Grant No.2022008)+1 种基金the Open Fund of State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures(Grant No.KF2023-06)S&T Program of Hebei(Grant No.225676162GH).
文摘In the parallel steering coordination control strategy for path tracking,it is difficult to match the current driver steering model using the fixed parameters with the actual driver,and the designed steering coordination control strategy under a single objective and simple conditions is difficult to adapt to the multi-dimensional state variables’input.In this paper,we propose a deep reinforcement learning algorithm-based multi-objective parallel human-machine steering coordination strategy for path tracking considering driver misoperation and external disturbance.Firstly,the driver steering mathematical model is constructed based on the driver preview characteristics and steering delay response,and the driver characteristic parameters are fitted after collecting the actual driver driving data.Secondly,considering that the vehicle is susceptible to the influence of external disturbances during the driving process,the Tube MPC(Tube Model Predictive Control)based path tracking steering controller is designed based on the vehicle system dynamics error model.After verifying that the driver steering model meets the driver steering operation characteristics,DQN(Deep Q-network),DDPG(Deep Deterministic Policy Gradient)and TD3(Twin Delayed Deep Deterministic Policy Gradient)deep reinforcement learning algorithms are utilized to design a multi-objective parallel steering coordination strategy which satisfies the multi-dimensional state variables’input of the vehicle.Finally,the tracking accuracy,lateral safety,human-machine conflict and driver steering load evaluation index are designed in different driver operation states and different road environments,and the performance of the parallel steering coordination control strategies with different deep reinforcement learning algorithms and fuzzy algorithms are compared by simulations and hardware in the loop experiments.The results show that the parallel steering collaborative strategy based on a deep reinforcement learning algorithm can more effectively assist the driver in tracking the target path under lateral wind interference and driver misoperation,and the TD3-based coordination control strategy has better overall performance.
基金supported by the National Key R&D Program of China(No.2023YFC3081200)the National Natural Science Foundation of China(No.42077264)the Scientific Research Project of PowerChina Huadong Engineering Corporation Limited(HDEC-2022-0301).
文摘Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.
文摘Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships.Networking structures are highly sensitive in social networks,requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks.In addition,they miss out on accurately identifying clusters.Since single-objective optimization cannot always generate accurate and comprehensive results,as multi-objective optimization can.Therefore,we utilized two objective functions that enable strong connections between communities and weak connections between them.In this study,we utilized the intra function,which has proven effective in state-of-the-art research studies.We proposed a new inter-function that has demonstrated its effectiveness by making the objective of detecting external connections between communities is to make them more distinct and sparse.Furthermore,we proposed a Multi-Objective community strength enhancement algorithm(MOCSE).The proposed algorithm is based on the framework of the Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),integrated with a new heuristic mutation strategy,community strength enhancement(CSE).The results demonstrate that the model is effective in accurately identifying community structures while also being computationally efficient.The performance measures used to evaluate the MOEA/D algorithm in our work are normalized mutual information(NMI)and modularity(Q).It was tested using five state-of-the-art algorithms on social networks,comprising real datasets(Zachary,Dolphin,Football,Krebs,SFI,Jazz,and Netscience),as well as twenty synthetic datasets.These results provide the robustness and practical value of the proposed algorithm in multi-objective community identification.
基金supported by Shanghai Municipal Natural Science Foundation,China(No.21ZR1446800)the National Natural Science Foundation of China(No.41877425)the Fundamental Research Funds for the Central Universities(No.226-2024-00052)。
文摘Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community assembly in virgin and aging MP plastispheres across different habitats is poorly understood.This study aims to assess the variations in bacterial community assembly across different niches and habitats with an in situ ex-periment,in which constructed forest wetland(FW),natural lake wetland(LW),and lotus pond wetland(LP)were habitats,and plastispheres of virgin and aging low-density polyethylene(LDPE)MPs,as well as surround-ing wetland soils were niches.Significant niche-related differences in bacterial communities were observed,with lower diversity and enrichment of potential plastic-degrading bacteria in the plastisphere than in the soil bacterial communities.Furthermore,habitat-related differences exerted a more pronounced influence on the beta-diversity patterns of the bacterial communities.The linear regression analyses indicated that the local species pool con-tributed more to bacterial community assembly in the LW wetland,whereas the relative abundance of species was the primary factor in the LP wetland.The null model analysis indicated that plastisphere bacterial communi-ties were predominantly driven by the stochastic process,with a more deterministic assembly observed in the LP wetland and soil bacterial communities.Additionally,the primary ecological process shaping plastisphere com-munities shifted from drift in the virgin LDPE to homogenising dispersal in the aging LDPE.This study provides new insights into the fate and ecological impacts of MPs in wetlands,thereby facilitating the effective regulations of plastic pollution.
基金financial y supported by the National Key Research and Development Program of China (2023YFD1900902)the Joint Funds of the Zhejiang Provincial Natural Science Foundation of China (LLSSZ24C030001)+1 种基金the Earmarked Fund for China Agriculture Research System (CARS-08-G-09)sponsored by the K.C.Wong Magna Fund of Ningbo University,China。
文摘Fungi play crucial roles in nutrient acquisition,plant growth promotion,and the enhancement of resistance to both abiotic and biotic stresses.However,studies on the fungal communities associated with peas (Pisum sativum L.) remain limited.In this study,we systematically investigated the ecological effects of host niches (soil,root,stem,leaf,and pod) and genotypes on the diversity and composition of fungal communities in peas using a multi-level approach that encompassed pattern recognition (β-diversity decomposition),mechanism validation (neutral community model testing),and dynamic tracking methods (migration pathway source-tracking).The results revealed that the dominant fungal phyla across niches and genotypes were Ascomycota,Basidiomycota,and Mortierellomycota,and the community structures of the soil–plant continuum were primarily determined by the pea niches rather than genotypes.β-diversity decomposition was largely attributed to species replacement rather than richness differences,indicating strong niche specificity and microbial replacement across microhabitats.Neutral model analysis revealed that stochastic processes influenced genotypeassociated communities,while deterministic processes played a dominant role in niche-based community assembly.Source-tracking analysis identified niche-to-niche fungal migration,with Erysiphe,Fusarium,Cephaliophora,Ascobolus,Alternaria,and Aspergillus as the key genera.Migration rates from exogenous to endogenous niches were low (1.3–61.5%),whereas those within exogenous (64.4–83.7%) or endogenous (73.9–96.4%) compartments were much higher,suggesting that the pea epidermis acts as a selective barrier that filters and enriches microbial communities prior to internal colonization.This study provides comprehensive insights into the mechanisms of host filtering,enrichment and microbial sourcing,which increases our understanding of the assembly rules of the pea-associated fungal microbiome.
文摘Professional learning communities(PLCs)offer essential contextual support for the development of foreign language teachers in higher education.The book Building Professional Learning Communities of Foreign Language Teachers in Higher Education,co-authored by Wen et al.(2021)systematically examines the necessity,practical measures,theoretical construction,and outcomes associated with building PLCs for university foreign language teachers.Notably,it introduces a research methodology rooted in local teacher education practices with Chinese characteristics—the dialectical research paradigm(DRP).This review introduces the content of the book,evaluates its contributions to teacher development,and explores its implications for future practice and research.
基金Under the auspices of the National Key Research and Development Program of China Science and Technology Cooperation Project of the Chinese and Russian Governments(No.2023YFE0111300)National Social Science Fund of China(No.23BGL204)Natural Science Foundation of Inner Mongolia(No.2022MS04001)。
文摘Prolonged droughts have emerged as a major impediment to the revitalization of pastoral regions worldwide because they significantly augment their susceptibility to the deleterious effects of global climate change,overgrazing,and land degradation.This study,conducted in 106 pastoral villages across 33 pastoral banners of Inner Mongolia Autonomous Region of China between August 2021 and October 2022,used a community resilience evaluation indicator system to assess drought resistance.By calculating a community resilience index,the research explored influencing factors and proposed countermeasures,aiming to enhance resilience to prolonged drought.The results revealed three key findings.1)Pastoral areas exhibited a limited degree of community resilience to drought disasters(overall score=0.28),with resilience levels forming a pyramid-shaped hierarchy.2)Dimensional analysis showed that resilience scores decreased sequentially across five domains:social(0.53)>cultural(0.44)>environmental(0.38)>economic(0.32)>management(0.27).These results highlight the crucial role of economic and management resilience in enhancing community resilience,particularly when accompanied by pre-and post-disaster government support and social security,both of which must be improved.3)Key factors influencing community resilience included geographical location,traffic accessibility,and frequency and severity of droughts.From a drought resilience perspective,targeted strategies and recommendations are proposed to provide novel and practical approaches for achieving sustainable development in pastoral areas and rural regions as a whole.
基金supported by the National Natural Science Foundation of China(No.42377083)the Natural Science Foundation of Sichuan Province,China(No.2025 ZNSFSC0433).
文摘In this work,ofloxacin(OFL),a kind of frequently detected antibiotic in groundwater,was selected to explore its impact(at ng/L-μg/L-level)on denitrification performance in an autotrophic denitrification system driven by pyrite/sulfur(FeS2/S0).Results showed that OFL restrained nitrate removal efficiency,and the inhibition degree was positively related to the concentration of OFL.After being exposed to increased OFL(200 ng/L-100μg/L)for 69 days,higher inhibition of electron transport activity(ETSA),enzyme activities of nitrate reductase(NAR),and nitrite reductase(NIR)were acquired.Meanwhile,the extracellular protein(PN)content of sludge samples was remarkably stimulated by OFL to resist the augmented toxicity.OFL contributed to increased microbial diversity and sulfur/sulfide oxidation functional genes in ng/L-level bioreactors,whereas led to a decline inμg/L level experiments.With OFL at concentrations of 200 ng/L and 100μg/L,the whole expression of 10 key denitrification functional genes was depressed,and the higher the OFL concentration,the lower the expression level.However,no significant proliferation of antibiotic resistance genes(ARGs)either in 200 ng/L-OFL or 100μg/L-OFL groups was observed.Two-factor correlation analysis results indicated that Thiobacillus,Anaerolineae,Anaerolineales,and Nitrospirae might be the main hosts of existing ARGs in this system.
文摘As a Burundian doctoral student at Nanjing University,my personal journey is closely intertwined with China’s development in the new era and the deepening China-Africa partnership.Recently,my experiences have given me a deeper appreciation of the importance of people-to-people exchanges between China and Africa.
文摘In the countryside of east Zhejiang Province,a quiet village has hit a home run.Xujiadai,once a place known for pig farming and environmental pollution,is drawing visitors from across China with a sport still uncommon in the country:baseball.
基金supported by the Research Funds of the Center for Big Data and Population Health of IHM(grant number JKS2022015)the Key Scientific Research Fund of the Anhui Provincial Education Department(grant number2023AH050610)the Anhui Natural Science Foundation(grant number 1808085QH252)。
文摘In 2021,approximately 537 million people suffered from diabetes mellitus(DM)globally,and this figure will increase to approximately 783 million within the next quarter-century.The increasing burden of DM is a pressing global public health issue.Therefore,the early identification of high-risk groups and implementation of effective intervention measures is imperative.
文摘Urinary tract infections(UTIs)are among the most prevalent pediatric bacterial infections,and undertreated episodes may lead to renal scarring,hypertension,or chronic kidney disease.Multidrug-resistant(MDR)Enterobacterales have been increasingly reported in children,with higher rates in Asian and Middle Eastern settings than in high-income countries[1,2].
基金supported in part by the National Natural Science Foundation of China(U181321461773369+2 种基金61903360)the Selfplanned Project of the State Key Laboratory of Robotics(2020-Z12)China Postdoctoral Science Foundation funded project(2019M661155)。
文摘Electromyography(EMG)has already been broadly used in human-machine interaction(HMI)applications.Determining how to decode the information inside EMG signals robustly and accurately is a key problem for which we urgently need a solution.Recently,many EMG pattern recognition tasks have been addressed using deep learning methods.In this paper,we analyze recent papers and present a literature review describing the role that deep learning plays in EMG-based HMI.An overview of typical network structures and processing schemes will be provided.Recent progress in typical tasks such as movement classification,joint angle prediction,and force/torque estimation will be introduced.New issues,including multimodal sensing,inter-subject/inter-session,and robustness toward disturbances will be discussed.We attempt to provide a comprehensive analysis of current research by discussing the advantages,challenges,and opportunities brought by deep learning.We hope that deep learning can aid in eliminating factors that hinder the development of EMG-based HMI systems.Furthermore,possible future directions will be presented to pave the way for future research.
基金financially supported by the Natural Science Foundation of China(Nos.22109120,62104170 and 82202757)Zhejiang Provincial Natural Science Foundation of China(Nos.LQ21B030002 and LY23F040001)。
文摘Hydrogel-based triboelectric nanoge nerator(TENG)has a promising applied prospect in wearable electronic devices.However,its low performance,poor stability,insufficient recyclability and inferior self-healing seriously hinder its development.Herein,we report a robust route to a liquid metal(LM)/polyvinyl alcohol(PVA)hydrogel-based TENG(LP-TENG).Owing to the intrinsically liquid feature of conductive LM within the flexible PVA hydrogel,the as-prepared LP-TENG exhibited comprehensiye advantages of adaptability,biocompatibility,outstanding electrical performance,superior stability,recyclability and diverse applications,which were unattainable by traditional systems.Concretely,the LP-TENG delivered appealing open circuit voltage of 250 V,short circuit current of 4μA and transferred charge of 120 nC with high stability,outperforming most advanced TENG systems.The LP-TENG was successfully employed for versatile applications with multifunctionality,including human motion detection,handwriting recognition,energy collection,message transmission and human-machine interaction.This work presents significant prospects for crafting advanced materials and devices in the fields of wearable electronics,flexible skin and smart robots.
基金the National Key R&D Project from Minister of Science and Technology(Grant No.2016YFA0202704)the Beijing Municipal Natural Science Foundation(Grant No.2212052)+1 种基金the Shanghai Sailing Program(Grant No.19S28101)the Fundamental Research Funds for the Central Universities(Grant No.19D128102).
文摘Combination flexible and stretchable textiles with self-powered sensors bring a novel insight into wearable functional electronics and cyber security in the era of Internet of Things.This work presents a highly flexible and self-powered fully fabric-based triboelectric nanogenerator(F-TENG)with sandwiched structure for biomechanical energy harvesting and real-time biometric authentication.The prepared F-TENG can power a digital watch by low-frequency motion and respond to the pressure change by the fall of leaves.A self-powered wearable keyboard(SPWK)is also fabricated by integrating large-area F-TENG sensor arrays,which not only can trace and record electrophysiological signals,but also can identify individuals’typing characteristics by means of the Haar wavelet.Based on these merits,the SPWK has promising applications in the realm of wearable electronics,self-powered sensors,cyber security,and artificial intelligences.
基金supported by the research project RORAS 2 of the Mediterranean Program funded by INRIA,France
文摘We outline problems and potential solutions for feasible human-machine interfaces using cable-based parallel manipulators for physiotherapy applications.From an engineering perspective,we discuss the design constraints related to acceptance by patients and physiotherapist users.To date,most designs have focused on mobile platforms that are designed to be operated as an end-effector connected to human limbs for direct patient interaction.Some specific examples are illustrated from the authors' experience with prototypes available at Laboratory of Robotics and Mechatronics (LARM),Italy.
基金The National Natural Science Foundation of China(No.51675098)。
文摘To reduce the complexity of the configuration and control strategy for shoulder rehabilitation exoskeleton,a 2R1R1P2R serial of shoulder exoskeleton based on gravity balance is proposed.Based on three basic rotatory shoulder joints,an exact kinematic constraint system can be formed between the exoskeleton and the upper arm by introducing a passive sliding pair and a center of glenohumeral(CGH)unpowered compensation mechanism,which realizes the human-machine kinematic compatibility.Gravity balance is used in the CGH compensation mechanism to provide shoulder joint support.Meanwhile,the motion of the compensation mechanism is pulled by doing reverse leading through the arm to realize the kinematic self-adaptive,which decreases control complexity.Besides,a simple and intuitive spring adjustment strategy is proposed to ensure the gravity balance of any prescribed quality.Furthermore,according to the influencing factors analysis of the scapulohumeral rhythm,the kinematic analysis of CGH mechanism is performed,which shows that the mechanism can fit the trajectory of CGH under various conditions.Finally,the dynamic simulation of the mechanism is carried out.Results indicate that the compensation torques are reduced to below 0.22 N·m,and the feasibility of the mechanism is also verified.
基金Supported by National Natural Science Foundation of China(Grant No.52075036)Key Technologies Research and Development Program of China(Grant No.2022YFC3302204).
文摘The Chinese express delivery industry processes nearly 110 billion items in 2022,averaging an annual growth rate of 200%.Among the various types of sorting systems used for handling express items,cross-belt sorting systems stand out as the most crucial.However,despite their high degree of automation,the workload for operators has intensified owing to the surging volume of express items.In the era of Industry 5.0,it is imperative to adopt new technologies that not only enhance worker welfare but also improve the efficiency of cross-belt systems.Striking a balance between efficiency in handling express items and operator well-being is challenging.Digital twin technology offers a promising solution in this respect.A realization method of a human-machine integrated digital twin is proposed in this study,enabling the interaction of biological human bodies,virtual human bodies,virtual equipment,and logistics equipment in a closed loop,thus setting an operating framework.Key technologies in the proposed framework include a collection of heterogeneous data from multiple sources,construction of the relationship between operator fatigue and operation efficiency based on physiological measurements,virtual model construction,and an online optimization module based on real-time simulation.The feasibility of the proposed method was verified in an express distribution center.
