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
The sorting system applies multi-sensor technology,PLC technology,pneumatic technology and frequency converter technology to realize the efficient automatic sorting of workpieces and solve the problem of automatic sor...The sorting system applies multi-sensor technology,PLC technology,pneumatic technology and frequency converter technology to realize the efficient automatic sorting of workpieces and solve the problem of automatic sorting of more complex shaped products.Through running test,the system has high efficiency,reliable operation,strong practicability,and great application value in automatic production lines such as mechanical processing,electronic assembly and article circulation.展开更多
With the rapid development of express logistics business side, the traditional sorting has been unable to meet the needs of the logistics courier logistics development. In this case, the article combined with RFID rad...With the rapid development of express logistics business side, the traditional sorting has been unable to meet the needs of the logistics courier logistics development. In this case, the article combined with RFID radio frequency technology, put forward new ideas on the transformation of traditional logistics sorted. By adding RFID tags and binding RFID tags on waybill number, Comparison test validate and affirm that the RFID technology of sorting system is usability and ease of use.展开更多
Identification,sorting,and sequencing of individual cells directly from in situ samples have great potential for in-depth analysis of the structure and function of microbiomes.In this work,based on an artificial intel...Identification,sorting,and sequencing of individual cells directly from in situ samples have great potential for in-depth analysis of the structure and function of microbiomes.In this work,based on an artificial intelligence(AI)-assisted object detection model for cell phenotype screening and a cross-interface contact method for single-cell exporting,we developed an automatic and index-based system called EasySort AUTO,where individual microbial cells are sorted and then packaged in a microdroplet and automatically exported in a precisely indexed,“One-Cell-One-Tube”manner.The target cell is automatically identified based on an AI-assisted object detection model and then mobilized via an optical tweezer for sorting.Then,a crossinterface contact microfluidic printing method that we developed enables the automated transfer of cells from the chip to the tube,which leads to coupling with subsequent single-cell culture or sequencing.The efficiency of the system for single-cell printing is>93%.The throughput of the system for single-cell printing is~120 cells/h.Moreover,>80%of single cells of both yeast and Escherichia coli are culturable,suggesting the superior preservation of cell viability during sorting.Finally,AI-assisted object detection supports automated sorting of target cells with high accuracy from mixed yeast samples,which was validated by downstream single-cell proliferation assays.The automation,index maintenance,and vitality preservation of EasySort AUTO suggest its excellent application potential for single-cell sorting.展开更多
Droplet microfluidics,which encapsulates individual cells within separate microreactors,has become an essential tool for single-cell phenotypic and genotypic analysis.However,the efficiency of single-cell encapsulatio...Droplet microfluidics,which encapsulates individual cells within separate microreactors,has become an essential tool for single-cell phenotypic and genotypic analysis.However,the efficiency of single-cell encapsulation is limited by the Poisson distribution governing the encapsulation process,resulting in most droplets being either empty or containing multiple cells.Traditional single-cell sorting methods typically rely on fluorescence labeling for identification,but this approach not only increases experimental costs and complexity but can also impact cell viability.Additionally,current label-free sorting methods still encounter difficulties in accurately detecting multicellular droplets and small cellular aggregates.To address these challenges,this paper proposes an intelligent sorting system that combines YOLOv8 object detection and BoTSORT tracking algorithms.This system enables real-time analysis of droplet images,facilitating precise identification,counting,and automated sorting of target droplets.To validate the system’s performance,polystyrene microspheres were used to simulate real cells in sorting tests.The results demonstrated that,under label-free conditions,the system significantly outperformed traditional fluorescence labeling methods in both classification accuracy and sorting efficiency.This system provides an effective,label-free solution for cell sorting,with potential applications in precision medicine,single-cell sequencing,and drug screening.展开更多
Elucidating the mechanisms underlying community assembly remains a central question in community ecology,especially in aquatic ecosystems disrupted by human activities.Understanding the causes and consequences of comm...Elucidating the mechanisms underlying community assembly remains a central question in community ecology,especially in aquatic ecosystems disrupted by human activities.Understanding the causes and consequences of community responses to changing environment is essential for revealing the ecological effects of anthropogenic disturbances and proposing practical strategies for ecological restoration.While stochastic dispersal and species sorting are known to influence local biological communities,most studies have focused on horizontal dispersal,often neglecting the vertical exchange of organisms between planktonic and sedimentary communities when studying stochastic dispersal.We used a highly disturbed urban river in Beijing as a model system to investigate the relative roles of stochastic dispersal versus species sorting driven by local pollution,as well as two components of stochastic dispersal,vertical exchange and horizontal dispersal,in structuring local bacterial communities.Our integrated analyses of planktonic and sedimentary bacterial communities revealed that,despite different spatial patterns along the river,both types of bacterial communities were primarily shaped by stochastic dispersal processes rather than species sorting influenced by the environmental gradient.Notably,in addition to the effect of horizontal dispersal along the river,the vertical exchange between planktonic and sedimentary bacterial communities significantly contributed to the formation of local communities.These findings suggest that both vertical exchange and horizontal dispersal should be considered when assessing the role of stochastic dispersal in shaping local community structure in microbial communities.展开更多
The somatotopic representation of specific body parts is a well-established spatial organizational principle in the primary somatosensory and motor cortices.
The need to transport goods across countries and islands has resulted in a high demand for commercial vessels.Owing to such trends,shipyards must efficiently produce ships to reduce production costs.Layout and materia...The need to transport goods across countries and islands has resulted in a high demand for commercial vessels.Owing to such trends,shipyards must efficiently produce ships to reduce production costs.Layout and material flow are among the crucial aspects determining the efficiency of the production at a shipyard.This paper presents the initial design optimization of a shipyard layout using Nondominated Sorting Algorithm-Ⅱ(NSGA-Ⅱ)to find the optimal configuration of workstations in a shipyard layout.The proposed method focuses on simultaneously minimizing two material handling costs,namely work-based material handling and duration-based material handling.NSGA-Ⅱ determines the order of workstations in the shipyard layout.The semiflexible bay structure is then used in the workstation placement process from the sequence formed in NSGA-Ⅱ into a complete design.Considering that this study is a case of multiobjective optimization,the performance for both objectives at each iteration is presented in a 3D graph.Results indicate that after 500 iterations,the optimal configuration yields a work-based MHC of 163670.0 WBM-units and a duration-based MHC of 34750 DBM-units.Starting from a random solution,the efficiency of NSGA-Ⅱ demonstrates significant improvements,achieving a 50.19%reduction in work-based MHC and a 48.58%reduction in duration-based MHC.展开更多
The belief rule-based(BRB)system has been popular in complexity system modeling due to its good interpretability.However,the current mainstream optimization methods of the BRB systems only focus on modeling accuracy b...The belief rule-based(BRB)system has been popular in complexity system modeling due to its good interpretability.However,the current mainstream optimization methods of the BRB systems only focus on modeling accuracy but ignore the interpretability.The single-objective optimization strategy has been applied in the interpretability-accuracy trade-off by inte-grating accuracy and interpretability into an optimization objec-tive.But the integration has a greater impact on optimization results with strong subjectivity.Thus,a multi-objective optimiza-tion framework in the modeling of BRB systems with inter-pretability-accuracy trade-off is proposed in this paper.Firstly,complexity and accuracy are taken as two independent opti-mization goals,and uniformity as a constraint to give the mathe-matical description.Secondly,a classical multi-objective opti-mization algorithm,nondominated sorting genetic algorithm II(NSGA-II),is utilized as an optimization tool to give a set of BRB systems with different accuracy and complexity.Finally,a pipeline leakage detection case is studied to verify the feasibility and effectiveness of the developed multi-objective optimization.The comparison illustrates that the proposed multi-objective optimization framework can effectively avoid the subjectivity of single-objective optimization,and has capability of joint optimiz-ing the structure and parameters of BRB systems with inter-pretability-accuracy trade-off.展开更多
The progress of modern industry has given rise to great requirements for network transmission latency and reliability in domains such as smart grid and intelligent driving.To address these challenges,the concept of Ti...The progress of modern industry has given rise to great requirements for network transmission latency and reliability in domains such as smart grid and intelligent driving.To address these challenges,the concept of Time-sensitive networking(TSN)is proposed by IEEE 802.1TSN working group.In order to achieve low latency,Cyclic queuing and forwarding(CQF)mechanism is introduced to schedule Timetriggered(TT)flows.In this paper,we construct a TSN model based on CQF and formulate the flow scheduling problem as an optimization problem aimed at maximizing the success rate of flow scheduling.The problem is tackled by a novel algorithm that makes full use of the characteristics and the relationship between the flows.Firstly,by K-means algorithm,the flows are initially partitioned into subsets based on their correlations.Subsequently,the flows within each subset are sorted by a new special criteria extracted from multiple features of flow.Finally,a flow offset selecting method based on load balance is used for resource mapping,so as to complete the process of flow scheduling.Experimental results demonstrate that the proposed algorithm exhibits significant advantages in terms of scheduling success rate and time efficiency.展开更多
The non-dominated sorting genetic algorithm （NSGA） is improved with the controlled elitism and dynamic crowding distance. A novel multi-objective optimization algorithm is obtained for wind turbine blades. As an exa...The non-dominated sorting genetic algorithm （NSGA） is improved with the controlled elitism and dynamic crowding distance. A novel multi-objective optimization algorithm is obtained for wind turbine blades. As an example, a 5 MW wind turbine blade design is presented by taking the maximum power coefficient and the minimum blade mass as the optimization objectives. The optimal results show that this algorithm has good performance in handling the multi-objective optimization of wind turbines, and it gives a Pareto-optimal solution set rather than the optimum solutions to the conventional multi objective optimization problems. The wind turbine blade optimization method presented in this paper provides a new and general algorithm for the multi-objective optimization of wind turbines.展开更多
The main function of electronic support measure system is to detect threating signals in order to take countermeasures against them. To accomplish this objective, a process of associating each interleaved pulse with i...The main function of electronic support measure system is to detect threating signals in order to take countermeasures against them. To accomplish this objective, a process of associating each interleaved pulse with its emitter must be done. This process is termed sorting or de-interleaving. A novel point symmetry based radar sorting (PSBRS) algorithm is addressed. In order to deal with all kinds of radar signals, the symmetry measure distance is used to cluster pulses instead of the conventional Euclidean distance. The reference points of the symmetrical clusters are initialized by the alternative fuzzy c-means (AFCM) algorithm to ameliorate the effects of noise and the false sorting. Besides, the density filtering (DF) algorithm is proposed to discard the noise pulses or clutter. The performance of the algorithm is evaluated under the effects of noise and missing pulses. It has been observed that the PSBRS algorithm can cope with a large number of noise pulses and it is completely independent of missing pulses. Finally, PSBRS is compared with some benchmark algorithms, and the simulation results reveal the feasibility and efficiency of the algorithm.展开更多
Under the background of increasingly scarce ore worldwide and increasingly fierce market competition,developing the mining industry could be strongly restricted.Intelligent ore sorting equipment not only improves ore ...Under the background of increasingly scarce ore worldwide and increasingly fierce market competition,developing the mining industry could be strongly restricted.Intelligent ore sorting equipment not only improves ore use and enhances the economic benefits of enterprises but also increases the ore grade and lessens the grinding cost and tailings production.However,long-term research on intelligent ore sorting equipment found that the factors affecting sorting efficiency mainly include ore information identification technology,equipment sorting actuator,and information processing algorithm.The high precision,strong anti-interference capability,and high speed of these factors guarantee the separation efficiency of intelligent ore sorting equipment.Color ore sorter,X-ray ore transmission sorter,dual-energy X-ray transmission ore sorter,X-ray fluorescence ore sorter,and near-infrared ore sorter have been successfully developed in accordance with the different characteristics of minerals while ensuring the accuracy of equipment sorting and improving the equipment sorting efficiency.With the continuous improvement of mine automation level,the application of online element rapid analysis technology with high speed,high precision,and strong anti-interference capability in intelligent ore sorting equipment will become an inevitable trend of equipment development in the future.Laser-induced breakdown spectroscopy,transientγneutron activation analysis,online Fourier transform infrared spectroscopy,and nuclear magnetic resonance techniques will promote the development of ore sorting equipment.In addition,the improvement and joint application of additional high-speed and high-precision operation algorithms(such as peak area,principal component analysis,artificial neural network,partial least squares,and Monte Carlo library least squares methods)are an essential part of the development of intelligent ore sorting equipment in the future.展开更多
The recycling of construction and demolition waste(CDW)remains an urgent problem to be solved.In the industry,raw CDW needs to be manually sorted.To achieve high efficiency and avoid the risks of manual sorting,a sort...The recycling of construction and demolition waste(CDW)remains an urgent problem to be solved.In the industry,raw CDW needs to be manually sorted.To achieve high efficiency and avoid the risks of manual sorting,a sorting robot can be designed to grasp and sort CDW on a conveyor belt.But dynamic grasping on the conveyor belt is a challenge.We collected location information with a three-dimensional camera and then evaluated the method of dynamic robotic grasping.This paper discusses the grasping strategy of rough processed CDW on the conveyor belt,and implements the function of grasping and sorting on the recycling line.Furthermore,two new mathematical models for a robotic locating system are established,the accuracy of the model is tested with Matlab,and the selected model is applied to actual working conditions to verify the sorting accuracy.Finally,the robot kinematics parameters are optimized to improve the sorting efficiency through experiments in a real system,and it was concluded that when the conveyor speed was kept at around 0.25 m/s,better sorting results could be achieved.Increasing the speed and shortening the acceleration/deceleration time would reach the maximum efficiency when the load would allow it.Currently,the sorting efficiency reached approximately 2000 pieces per hour,showing a high accuracy.展开更多
Sensor-based ore sorting is a technology used to classify high-grade mineralized rocks from low-grade waste rocks to reduce operation costs.Many ore-sorting algorithms using color images have been proposed in the past...Sensor-based ore sorting is a technology used to classify high-grade mineralized rocks from low-grade waste rocks to reduce operation costs.Many ore-sorting algorithms using color images have been proposed in the past,but only some validate their results using mineral grades or optimize the algorithms to classify rocks in real-time.This paper presents an ore-sorting algorithm based on image processing and machine learning that is able to classify rocks from a gold and silver mine based on their grade.The algorithm is composed of four main stages:(1)image segmentation and partition,(2)color and texture feature extraction,(3)sub-image classification using neural networks,and(4)a voting system to determine the overall class of the rock.The algorithm was trained using images of rocks that a geologist manually classified according to their mineral content and then was validated using a different set of rocks analyzed in a laboratory to determine their gold and silver grades.The proposed method achieved a Matthews correlation coefficient of 0.961 points,higher than other classification algorithms based on support vector machines and convolutional neural networks,and a processing time under 44 ms,promising for real-time ore sorting applications.展开更多
A multi-objective optimization model considering both reliability and maintenance cost is proposed to solve the contradiction between reliability and maintenance cost in high-speed railway catenary system maintenance ...A multi-objective optimization model considering both reliability and maintenance cost is proposed to solve the contradiction between reliability and maintenance cost in high-speed railway catenary system maintenance activities.The non-dominated sorting genetic algorithm 2(NSGA2)is applied to multi-objective optimization,and the optimization result is a set of Pareto solutions.Firstly,multistate failure mode analysis is conducted for the main devices leading to the failure of catenary,and then the reliability and failure mode of the whole catenary system is analyzed.The mathematical relationship between system reliability and maintenance cost is derived considering the existing catenary preventive maintenance mode to improve the reliability of the system.Secondly,an improved NSGA2(INSGA2)is proposed,which strengths population diversity by improving selection operator,and introduces local search strategy to ensure that population distribution is more uniform.The comparison results of the two algorithms before and after improvement on the zero-ductility transition(ZDT)series functions show that the population diversity is better and the solution is more uniform using INSGA2.Finally,the INSGA2 is applied to multi-objective optimization of system reliability and maintenance cost in different maintenance periods.The decision-makers can choose the reasonable solutions as the maintenance plans in the optimization results by weighing the relationship between the system reliability and the maintenance cost.The selected maintenance plans can ensure the lowest maintenance cost while the system reliability is as high as possible.展开更多
Incomplete lineage sorting and introgression are 2 major and nonexclusive causes of specieslevel non-monophyly.Distinguishing between these 2 processes is notoriously difficult because they can generate similar geneti...Incomplete lineage sorting and introgression are 2 major and nonexclusive causes of specieslevel non-monophyly.Distinguishing between these 2 processes is notoriously difficult because they can generate similar genetic signatures.Previous studies have suggested that 2 closely related duck species,the Chinese spot-billed duck Anas zonorhyncha and the mallard A.platyrhynchosvjere polyphyletically intermixed.Here,we utilized a wide geographical sampling,multilocus data and a coalescent-based model to revisit this system.Our study confirms the finding that Chinese spot-billed ducks and Mallards are not monophyletic.There was no apparent interspecific differentiation across loci except those at the mitochondrial DNA(mtDNA)control region and the Z chromosome(CHD1Z).Based on an isolation-with-migration model and the geographical distribution of lineages,we suggest that both introgression and incomplete lineage sorting might contribute to the observed non-monophyly of the 2 closely related duck species.The mtDNA introgression was asymmetric,with high gene flow from Chinese spot-billed ducks to Mallards and negligible gene flow in the opposite direction.Given that the 2 duck species are phenotypically distinctive but weakly genetically differentiated,future work based on genomescale data is necessary to uncover genomic regions that are involved in divergence,and this work may provide further insights into the evolutionary histories of the 2 species and other waterfowls.展开更多
A novel class of periodically changing features hidden in radar pulse sequence environment,named G features,is proposed.Combining fractal theory and Hilbert-Huang transform,the features are extracted using changing ch...A novel class of periodically changing features hidden in radar pulse sequence environment,named G features,is proposed.Combining fractal theory and Hilbert-Huang transform,the features are extracted using changing characteristics of pulse parameters in radar emitter signals.The features can be applied in modern complex electronic warfare environment to address the issue of signal sorting when radar emitter pulse signal parameters severely or even completely overlap.Experiment results show that the proposed feature class and feature extraction method can discriminate periodically changing pulse sequence signal sorting features from radar pulse signal flow with complex variant features,therefore provide a new methodology for signal sorting.展开更多
The structure parameters of 6-degree of freedom(DOF)vibration isolation platform have a significant effect on its performance.To make the designed vibration isolation platform perform well,non-dominanted sorting genet...The structure parameters of 6-degree of freedom(DOF)vibration isolation platform have a significant effect on its performance.To make the designed vibration isolation platform perform well,non-dominanted sorting genetic algorithm version II(NSGA-II)was applied to optimize its structure based on the transfer matrix method for multibody systems.Firstly,the Jacobian matrix of 6-DOF vibration isolation platform was solved based on kinematics.Secondly,the transfer equation of 6-DOF vibration isolation system was established by the linear transfer matrix method for multibody systems.And the formula of its natural frequency was derived according to the boundary conditions of the system.Thirdly,the manipulability index was constructed based on a dimensionless Jacobian matrix.And a new performance index function was established considering the influence of dynamic isotropic and legs mass.Fourthly,genetic algorithm(GA)and NSGA-II were used to optimize the structure of the 6-DOF vibration isolation platform under the same conditions,respectively.It showed that NSGA-II had higher optimization efficiency,better calculation accuracy and shorter optimization time than that of GA.Finally,NSGA-II was adopted for multi-objective optimization design of 6-DOF vibration isolation platform based on the constraint conditions.Optimal Pareto solutions were obtained,which provides structural parameters for subsequent design work.Therefore,the proposed optimization method and the performance index in this paper provide a theoretical basis for the optimal design of relevant vibration isolation mechanism.展开更多
In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed...In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed, and the performance of the NSQPSO is evaluated through five classical benchmark functions. The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value. Therefore, QPSO is used as the evolutionary method of the proposed NSQPSO. Also NSQPSO is used to solve cognitive radio spectrum allocation problem. The methods to complete spectrum allocation in previous literature only consider one objective, i.e. network utilization or fairness, but the proposed NSQPSO method, can consider both network utilization and fairness simultaneously through obtaining Pareto front solutions. Cognitive radio systems can select one solution from the Pareto front solutions according to the weight of network reward and fairness. If one weight is unit and the other is zero, then it becomes single objective optimization, so the proposed NSQPSO method has a much wider application range. The experimental research results show that the NSQPS can obtain the same non-dominated solutions as exhaustive search but takes much less time in small dimensions; while in large dimensions, where the problem cannot be solved by exhaustive search, the NSQPSO can still solve the problem, which proves the effectiveness of NSQPSO.展开更多
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.
基金City College of Dongguan University of Technology Youth Teacher Development Fund(2019QJY003Z)Key Cultivating Disciplines of Guangdong Province(Document No.45,2017)City College of Dongguan University of Technology Youth Teacher Development Fund(2020QJY001Z).
文摘The sorting system applies multi-sensor technology,PLC technology,pneumatic technology and frequency converter technology to realize the efficient automatic sorting of workpieces and solve the problem of automatic sorting of more complex shaped products.Through running test,the system has high efficiency,reliable operation,strong practicability,and great application value in automatic production lines such as mechanical processing,electronic assembly and article circulation.
文摘With the rapid development of express logistics business side, the traditional sorting has been unable to meet the needs of the logistics courier logistics development. In this case, the article combined with RFID radio frequency technology, put forward new ideas on the transformation of traditional logistics sorted. By adding RFID tags and binding RFID tags on waybill number, Comparison test validate and affirm that the RFID technology of sorting system is usability and ease of use.
基金the National Key R&D Program of China(Grant No.2021YFC2101100).
文摘Identification,sorting,and sequencing of individual cells directly from in situ samples have great potential for in-depth analysis of the structure and function of microbiomes.In this work,based on an artificial intelligence(AI)-assisted object detection model for cell phenotype screening and a cross-interface contact method for single-cell exporting,we developed an automatic and index-based system called EasySort AUTO,where individual microbial cells are sorted and then packaged in a microdroplet and automatically exported in a precisely indexed,“One-Cell-One-Tube”manner.The target cell is automatically identified based on an AI-assisted object detection model and then mobilized via an optical tweezer for sorting.Then,a crossinterface contact microfluidic printing method that we developed enables the automated transfer of cells from the chip to the tube,which leads to coupling with subsequent single-cell culture or sequencing.The efficiency of the system for single-cell printing is>93%.The throughput of the system for single-cell printing is~120 cells/h.Moreover,>80%of single cells of both yeast and Escherichia coli are culturable,suggesting the superior preservation of cell viability during sorting.Finally,AI-assisted object detection supports automated sorting of target cells with high accuracy from mixed yeast samples,which was validated by downstream single-cell proliferation assays.The automation,index maintenance,and vitality preservation of EasySort AUTO suggest its excellent application potential for single-cell sorting.
文摘Droplet microfluidics,which encapsulates individual cells within separate microreactors,has become an essential tool for single-cell phenotypic and genotypic analysis.However,the efficiency of single-cell encapsulation is limited by the Poisson distribution governing the encapsulation process,resulting in most droplets being either empty or containing multiple cells.Traditional single-cell sorting methods typically rely on fluorescence labeling for identification,but this approach not only increases experimental costs and complexity but can also impact cell viability.Additionally,current label-free sorting methods still encounter difficulties in accurately detecting multicellular droplets and small cellular aggregates.To address these challenges,this paper proposes an intelligent sorting system that combines YOLOv8 object detection and BoTSORT tracking algorithms.This system enables real-time analysis of droplet images,facilitating precise identification,counting,and automated sorting of target droplets.To validate the system’s performance,polystyrene microspheres were used to simulate real cells in sorting tests.The results demonstrated that,under label-free conditions,the system significantly outperformed traditional fluorescence labeling methods in both classification accuracy and sorting efficiency.This system provides an effective,label-free solution for cell sorting,with potential applications in precision medicine,single-cell sequencing,and drug screening.
基金supported by the National Natural Science Foundation of China(No.32471608)the Open Project of Key Laboratory of Environmental Biotechnology,CAS(No.kf2020002)Yunnan Collaborative Innovation Center for Plateau Lake Ecology and Environmental Health.
文摘Elucidating the mechanisms underlying community assembly remains a central question in community ecology,especially in aquatic ecosystems disrupted by human activities.Understanding the causes and consequences of community responses to changing environment is essential for revealing the ecological effects of anthropogenic disturbances and proposing practical strategies for ecological restoration.While stochastic dispersal and species sorting are known to influence local biological communities,most studies have focused on horizontal dispersal,often neglecting the vertical exchange of organisms between planktonic and sedimentary communities when studying stochastic dispersal.We used a highly disturbed urban river in Beijing as a model system to investigate the relative roles of stochastic dispersal versus species sorting driven by local pollution,as well as two components of stochastic dispersal,vertical exchange and horizontal dispersal,in structuring local bacterial communities.Our integrated analyses of planktonic and sedimentary bacterial communities revealed that,despite different spatial patterns along the river,both types of bacterial communities were primarily shaped by stochastic dispersal processes rather than species sorting influenced by the environmental gradient.Notably,in addition to the effect of horizontal dispersal along the river,the vertical exchange between planktonic and sedimentary bacterial communities significantly contributed to the formation of local communities.These findings suggest that both vertical exchange and horizontal dispersal should be considered when assessing the role of stochastic dispersal in shaping local community structure in microbial communities.
文摘The somatotopic representation of specific body parts is a well-established spatial organizational principle in the primary somatosensory and motor cortices.
基金Supported by Direktorat Riset dan Pengembangan(Directorate of Research and Development)Universitas Indonesia(NKB-690/UN2.RST/HKP.05.00/2022).
文摘The need to transport goods across countries and islands has resulted in a high demand for commercial vessels.Owing to such trends,shipyards must efficiently produce ships to reduce production costs.Layout and material flow are among the crucial aspects determining the efficiency of the production at a shipyard.This paper presents the initial design optimization of a shipyard layout using Nondominated Sorting Algorithm-Ⅱ(NSGA-Ⅱ)to find the optimal configuration of workstations in a shipyard layout.The proposed method focuses on simultaneously minimizing two material handling costs,namely work-based material handling and duration-based material handling.NSGA-Ⅱ determines the order of workstations in the shipyard layout.The semiflexible bay structure is then used in the workstation placement process from the sequence formed in NSGA-Ⅱ into a complete design.Considering that this study is a case of multiobjective optimization,the performance for both objectives at each iteration is presented in a 3D graph.Results indicate that after 500 iterations,the optimal configuration yields a work-based MHC of 163670.0 WBM-units and a duration-based MHC of 34750 DBM-units.Starting from a random solution,the efficiency of NSGA-Ⅱ demonstrates significant improvements,achieving a 50.19%reduction in work-based MHC and a 48.58%reduction in duration-based MHC.
基金supported by the National Natural Science Foundation of China(71901212)the Science and Technology Innovation Program of Hunan Province(2020RC4046).
文摘The belief rule-based(BRB)system has been popular in complexity system modeling due to its good interpretability.However,the current mainstream optimization methods of the BRB systems only focus on modeling accuracy but ignore the interpretability.The single-objective optimization strategy has been applied in the interpretability-accuracy trade-off by inte-grating accuracy and interpretability into an optimization objec-tive.But the integration has a greater impact on optimization results with strong subjectivity.Thus,a multi-objective optimiza-tion framework in the modeling of BRB systems with inter-pretability-accuracy trade-off is proposed in this paper.Firstly,complexity and accuracy are taken as two independent opti-mization goals,and uniformity as a constraint to give the mathe-matical description.Secondly,a classical multi-objective opti-mization algorithm,nondominated sorting genetic algorithm II(NSGA-II),is utilized as an optimization tool to give a set of BRB systems with different accuracy and complexity.Finally,a pipeline leakage detection case is studied to verify the feasibility and effectiveness of the developed multi-objective optimization.The comparison illustrates that the proposed multi-objective optimization framework can effectively avoid the subjectivity of single-objective optimization,and has capability of joint optimiz-ing the structure and parameters of BRB systems with inter-pretability-accuracy trade-off.
基金supported by Science and Technology Project of State Grid Corporation Headquarters under Grant 5108-202218280A-2-170-XG(Development and Application of Power Time-Sensitive Network Switching Chip。
文摘The progress of modern industry has given rise to great requirements for network transmission latency and reliability in domains such as smart grid and intelligent driving.To address these challenges,the concept of Time-sensitive networking(TSN)is proposed by IEEE 802.1TSN working group.In order to achieve low latency,Cyclic queuing and forwarding(CQF)mechanism is introduced to schedule Timetriggered(TT)flows.In this paper,we construct a TSN model based on CQF and formulate the flow scheduling problem as an optimization problem aimed at maximizing the success rate of flow scheduling.The problem is tackled by a novel algorithm that makes full use of the characteristics and the relationship between the flows.Firstly,by K-means algorithm,the flows are initially partitioned into subsets based on their correlations.Subsequently,the flows within each subset are sorted by a new special criteria extracted from multiple features of flow.Finally,a flow offset selecting method based on load balance is used for resource mapping,so as to complete the process of flow scheduling.Experimental results demonstrate that the proposed algorithm exhibits significant advantages in terms of scheduling success rate and time efficiency.
基金Project supported by the National Basic Research Program of China (973 Program) (No. 2007CB714600)
文摘The non-dominated sorting genetic algorithm （NSGA） is improved with the controlled elitism and dynamic crowding distance. A novel multi-objective optimization algorithm is obtained for wind turbine blades. As an example, a 5 MW wind turbine blade design is presented by taking the maximum power coefficient and the minimum blade mass as the optimization objectives. The optimal results show that this algorithm has good performance in handling the multi-objective optimization of wind turbines, and it gives a Pareto-optimal solution set rather than the optimum solutions to the conventional multi objective optimization problems. The wind turbine blade optimization method presented in this paper provides a new and general algorithm for the multi-objective optimization of wind turbines.
基金supported by the National Natural Science Foundation of China(61172116)
文摘The main function of electronic support measure system is to detect threating signals in order to take countermeasures against them. To accomplish this objective, a process of associating each interleaved pulse with its emitter must be done. This process is termed sorting or de-interleaving. A novel point symmetry based radar sorting (PSBRS) algorithm is addressed. In order to deal with all kinds of radar signals, the symmetry measure distance is used to cluster pulses instead of the conventional Euclidean distance. The reference points of the symmetrical clusters are initialized by the alternative fuzzy c-means (AFCM) algorithm to ameliorate the effects of noise and the false sorting. Besides, the density filtering (DF) algorithm is proposed to discard the noise pulses or clutter. The performance of the algorithm is evaluated under the effects of noise and missing pulses. It has been observed that the PSBRS algorithm can cope with a large number of noise pulses and it is completely independent of missing pulses. Finally, PSBRS is compared with some benchmark algorithms, and the simulation results reveal the feasibility and efficiency of the algorithm.
基金supported by the National Science and Technology Support Program of China(No.2012BAC11B07)the Jiangxi Science and Technology Innovation Base Plan(No.20212BCD42017)。
文摘Under the background of increasingly scarce ore worldwide and increasingly fierce market competition,developing the mining industry could be strongly restricted.Intelligent ore sorting equipment not only improves ore use and enhances the economic benefits of enterprises but also increases the ore grade and lessens the grinding cost and tailings production.However,long-term research on intelligent ore sorting equipment found that the factors affecting sorting efficiency mainly include ore information identification technology,equipment sorting actuator,and information processing algorithm.The high precision,strong anti-interference capability,and high speed of these factors guarantee the separation efficiency of intelligent ore sorting equipment.Color ore sorter,X-ray ore transmission sorter,dual-energy X-ray transmission ore sorter,X-ray fluorescence ore sorter,and near-infrared ore sorter have been successfully developed in accordance with the different characteristics of minerals while ensuring the accuracy of equipment sorting and improving the equipment sorting efficiency.With the continuous improvement of mine automation level,the application of online element rapid analysis technology with high speed,high precision,and strong anti-interference capability in intelligent ore sorting equipment will become an inevitable trend of equipment development in the future.Laser-induced breakdown spectroscopy,transientγneutron activation analysis,online Fourier transform infrared spectroscopy,and nuclear magnetic resonance techniques will promote the development of ore sorting equipment.In addition,the improvement and joint application of additional high-speed and high-precision operation algorithms(such as peak area,principal component analysis,artificial neural network,partial least squares,and Monte Carlo library least squares methods)are an essential part of the development of intelligent ore sorting equipment in the future.
基金The authors are thankful for the financial support provided by the Science and Technology Project of Quanzhou(Nos.2018C100R and 2019G003)the Science and Technology Cooperation Program of Quanzhou(No.2018C001)+1 种基金the Science and Technology Cooperation Program of Fujian(No.2018I1006)the Joint Innovation Project of Industrial Technology in the Fujian Province,and Subsidized Project for Postgraduates′Innovative Fund in Scientific Research of Huaqiao University.
文摘The recycling of construction and demolition waste(CDW)remains an urgent problem to be solved.In the industry,raw CDW needs to be manually sorted.To achieve high efficiency and avoid the risks of manual sorting,a sorting robot can be designed to grasp and sort CDW on a conveyor belt.But dynamic grasping on the conveyor belt is a challenge.We collected location information with a three-dimensional camera and then evaluated the method of dynamic robotic grasping.This paper discusses the grasping strategy of rough processed CDW on the conveyor belt,and implements the function of grasping and sorting on the recycling line.Furthermore,two new mathematical models for a robotic locating system are established,the accuracy of the model is tested with Matlab,and the selected model is applied to actual working conditions to verify the sorting accuracy.Finally,the robot kinematics parameters are optimized to improve the sorting efficiency through experiments in a real system,and it was concluded that when the conveyor speed was kept at around 0.25 m/s,better sorting results could be achieved.Increasing the speed and shortening the acceleration/deceleration time would reach the maximum efficiency when the load would allow it.Currently,the sorting efficiency reached approximately 2000 pieces per hour,showing a high accuracy.
文摘Sensor-based ore sorting is a technology used to classify high-grade mineralized rocks from low-grade waste rocks to reduce operation costs.Many ore-sorting algorithms using color images have been proposed in the past,but only some validate their results using mineral grades or optimize the algorithms to classify rocks in real-time.This paper presents an ore-sorting algorithm based on image processing and machine learning that is able to classify rocks from a gold and silver mine based on their grade.The algorithm is composed of four main stages:(1)image segmentation and partition,(2)color and texture feature extraction,(3)sub-image classification using neural networks,and(4)a voting system to determine the overall class of the rock.The algorithm was trained using images of rocks that a geologist manually classified according to their mineral content and then was validated using a different set of rocks analyzed in a laboratory to determine their gold and silver grades.The proposed method achieved a Matthews correlation coefficient of 0.961 points,higher than other classification algorithms based on support vector machines and convolutional neural networks,and a processing time under 44 ms,promising for real-time ore sorting applications.
文摘A multi-objective optimization model considering both reliability and maintenance cost is proposed to solve the contradiction between reliability and maintenance cost in high-speed railway catenary system maintenance activities.The non-dominated sorting genetic algorithm 2(NSGA2)is applied to multi-objective optimization,and the optimization result is a set of Pareto solutions.Firstly,multistate failure mode analysis is conducted for the main devices leading to the failure of catenary,and then the reliability and failure mode of the whole catenary system is analyzed.The mathematical relationship between system reliability and maintenance cost is derived considering the existing catenary preventive maintenance mode to improve the reliability of the system.Secondly,an improved NSGA2(INSGA2)is proposed,which strengths population diversity by improving selection operator,and introduces local search strategy to ensure that population distribution is more uniform.The comparison results of the two algorithms before and after improvement on the zero-ductility transition(ZDT)series functions show that the population diversity is better and the solution is more uniform using INSGA2.Finally,the INSGA2 is applied to multi-objective optimization of system reliability and maintenance cost in different maintenance periods.The decision-makers can choose the reasonable solutions as the maintenance plans in the optimization results by weighing the relationship between the system reliability and the maintenance cost.The selected maintenance plans can ensure the lowest maintenance cost while the system reliability is as high as possible.
基金the National Natural Science Foundation of China(No.31401969,31772480)the Natural Science Foundation of Jiangxi Province(No.20161BAB214158).
文摘Incomplete lineage sorting and introgression are 2 major and nonexclusive causes of specieslevel non-monophyly.Distinguishing between these 2 processes is notoriously difficult because they can generate similar genetic signatures.Previous studies have suggested that 2 closely related duck species,the Chinese spot-billed duck Anas zonorhyncha and the mallard A.platyrhynchosvjere polyphyletically intermixed.Here,we utilized a wide geographical sampling,multilocus data and a coalescent-based model to revisit this system.Our study confirms the finding that Chinese spot-billed ducks and Mallards are not monophyletic.There was no apparent interspecific differentiation across loci except those at the mitochondrial DNA(mtDNA)control region and the Z chromosome(CHD1Z).Based on an isolation-with-migration model and the geographical distribution of lineages,we suggest that both introgression and incomplete lineage sorting might contribute to the observed non-monophyly of the 2 closely related duck species.The mtDNA introgression was asymmetric,with high gene flow from Chinese spot-billed ducks to Mallards and negligible gene flow in the opposite direction.Given that the 2 duck species are phenotypically distinctive but weakly genetically differentiated,future work based on genomescale data is necessary to uncover genomic regions that are involved in divergence,and this work may provide further insights into the evolutionary histories of the 2 species and other waterfowls.
基金supported by the National Natural Science Foundation of China (60872108)the Postdoctoral Science Foundation of China(200902411+3 种基金20080430903)Heilongjiang Postdoctoral Financial Assistance (LBH-Z08129)the Scientific and Technological Creative Talents Special Research Foundation of Harbin Municipality (2008RFQXG030)Central University Basic Research Professional Expenses Special Fund Project
文摘A novel class of periodically changing features hidden in radar pulse sequence environment,named G features,is proposed.Combining fractal theory and Hilbert-Huang transform,the features are extracted using changing characteristics of pulse parameters in radar emitter signals.The features can be applied in modern complex electronic warfare environment to address the issue of signal sorting when radar emitter pulse signal parameters severely or even completely overlap.Experiment results show that the proposed feature class and feature extraction method can discriminate periodically changing pulse sequence signal sorting features from radar pulse signal flow with complex variant features,therefore provide a new methodology for signal sorting.
基金supported by the National Natural Science Foundation of China(Grant 51975298)the Natural Science Foundation of Jiangsu Province(Grant BK20181301)the National Science Foundation of China(Grant 11874303).
文摘The structure parameters of 6-degree of freedom(DOF)vibration isolation platform have a significant effect on its performance.To make the designed vibration isolation platform perform well,non-dominanted sorting genetic algorithm version II(NSGA-II)was applied to optimize its structure based on the transfer matrix method for multibody systems.Firstly,the Jacobian matrix of 6-DOF vibration isolation platform was solved based on kinematics.Secondly,the transfer equation of 6-DOF vibration isolation system was established by the linear transfer matrix method for multibody systems.And the formula of its natural frequency was derived according to the boundary conditions of the system.Thirdly,the manipulability index was constructed based on a dimensionless Jacobian matrix.And a new performance index function was established considering the influence of dynamic isotropic and legs mass.Fourthly,genetic algorithm(GA)and NSGA-II were used to optimize the structure of the 6-DOF vibration isolation platform under the same conditions,respectively.It showed that NSGA-II had higher optimization efficiency,better calculation accuracy and shorter optimization time than that of GA.Finally,NSGA-II was adopted for multi-objective optimization design of 6-DOF vibration isolation platform based on the constraint conditions.Optimal Pareto solutions were obtained,which provides structural parameters for subsequent design work.Therefore,the proposed optimization method and the performance index in this paper provide a theoretical basis for the optimal design of relevant vibration isolation mechanism.
基金Foundation item： Projects（61102106, 61102105） supported by the National Natural Science Foundation of China Project（2013M530148） supported by China Postdoctoral Science Foundation Project（HEUCF120806） supported by the Fundamental Research Funds for the Central Universities of China
文摘In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed, and the performance of the NSQPSO is evaluated through five classical benchmark functions. The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value. Therefore, QPSO is used as the evolutionary method of the proposed NSQPSO. Also NSQPSO is used to solve cognitive radio spectrum allocation problem. The methods to complete spectrum allocation in previous literature only consider one objective, i.e. network utilization or fairness, but the proposed NSQPSO method, can consider both network utilization and fairness simultaneously through obtaining Pareto front solutions. Cognitive radio systems can select one solution from the Pareto front solutions according to the weight of network reward and fairness. If one weight is unit and the other is zero, then it becomes single objective optimization, so the proposed NSQPSO method has a much wider application range. The experimental research results show that the NSQPS can obtain the same non-dominated solutions as exhaustive search but takes much less time in small dimensions; while in large dimensions, where the problem cannot be solved by exhaustive search, the NSQPSO can still solve the problem, which proves the effectiveness of NSQPSO.
