Ship motions induced by waves have a significant impact on the efficiency and safety of offshore operations.Real-time prediction of ship motions in the next few seconds plays a crucial role in performing sensitive act...Ship motions induced by waves have a significant impact on the efficiency and safety of offshore operations.Real-time prediction of ship motions in the next few seconds plays a crucial role in performing sensitive activities.However,the obvious memory effect of ship motion time series brings certain difficulty to rapid and accurate prediction.Therefore,a real-time framework based on the Long-Short Term Memory(LSTM)neural network model is proposed to predict ship motions in regular and irregular head waves.A 15000 TEU container ship model is employed to illustrate the proposed framework.The numerical implementation and the real-time ship motion prediction in irregular head waves corresponding to the different time scales are carried out based on the container ship model.The related experimental data were employed to verify the numerical simulation results.The results show that the proposed method is more robust than the classical extreme short-term prediction method based on potential flow theory in the prediction of nonlinear ship motions.展开更多
Controlled laboratory experiments are proved to be a valuable tool for investigating changes in underground physical properties and the related response of surface geophysical signals.The self-potential(SP)method is w...Controlled laboratory experiments are proved to be a valuable tool for investigating changes in underground physical properties and the related response of surface geophysical signals.The self-potential(SP)method is widely used in mineral resource exploration due to its direct correlation with underground electrochemical gradients.This paper presented the design and construction of an experimental platform based on a multi-channel SP monitoring system.The proposed platform was used to monitor the anodizing corrosion process of different metal blocks from a laboratory perspective,record the real-time SP signal generated by the redox reaction,as well as investigate the geobattery mechanism associated with the natural polarization process of metal mineral resources.The experimental results demonstrate that the constructed SP monitoring platform effectively captures time-series SP signals and provides direct laboratory evidence for the geobattery model.The measured SP data were quantitatively interpreted using the simulated annealing algorithm,and the inversion results closely match the real model.This finding highlights the potential of the SP method as a promising tool for determining the location and spatial distribution of underground polarizers.The study holds reference value for the exploration and exploitation of mineral resources in both terrestrial and marine environments.展开更多
[Objective]Real-time monitoring of cow ruminant behavior is of paramount importance for promptly obtaining relevant information about cow health and predicting cow diseases.Currently,various strategies have been propo...[Objective]Real-time monitoring of cow ruminant behavior is of paramount importance for promptly obtaining relevant information about cow health and predicting cow diseases.Currently,various strategies have been proposed for monitoring cow ruminant behavior,including video surveillance,sound recognition,and sensor monitoring methods.How‐ever,the application of edge device gives rise to the issue of inadequate real-time performance.To reduce the volume of data transmission and cloud computing workload while achieving real-time monitoring of dairy cow rumination behavior,a real-time monitoring method was proposed for cow ruminant behavior based on edge computing.[Methods]Autono‐mously designed edge devices were utilized to collect and process six-axis acceleration signals from cows in real-time.Based on these six-axis data,two distinct strategies,federated edge intelligence and split edge intelligence,were investigat‐ed for the real-time recognition of cow ruminant behavior.Focused on the real-time recognition method for cow ruminant behavior leveraging federated edge intelligence,the CA-MobileNet v3 network was proposed by enhancing the MobileNet v3 network with a collaborative attention mechanism.Additionally,a federated edge intelligence model was designed uti‐lizing the CA-MobileNet v3 network and the FedAvg federated aggregation algorithm.In the study on split edge intelli‐gence,a split edge intelligence model named MobileNet-LSTM was designed by integrating the MobileNet v3 network with a fusion collaborative attention mechanism and the Bi-LSTM network.[Results and Discussions]Through compara‐tive experiments with MobileNet v3 and MobileNet-LSTM,the federated edge intelligence model based on CA-Mo‐bileNet v3 achieved an average Precision rate,Recall rate,F1-Score,Specificity,and Accuracy of 97.1%,97.9%,97.5%,98.3%,and 98.2%,respectively,yielding the best recognition performance.[Conclusions]It is provided a real-time and effective method for monitoring cow ruminant behavior,and the proposed federated edge intelligence model can be ap‐plied in practical settings.展开更多
An in-memory storage system provides submillisecond latency and improves the concurrency of user applications by caching data into memory from external storage.Fault tolerance of in-memory storage systems is essential...An in-memory storage system provides submillisecond latency and improves the concurrency of user applications by caching data into memory from external storage.Fault tolerance of in-memory storage systems is essential,as the loss of cached data requires access to data from external storage,which evidently increases the response latency.Typically,replication and erasure code(EC)are two fault-tolerant schemes that pose different trade-offs between access performance and storage usage.To help make the best performance and space trade-off,we design ElasticMem,a hybrid fault-tolerant distributed in-memory storage system that supports elastic redundancy transition to dynamically change the fault-tolerant scheme.ElasticMem exploits a novel EC-oriented replication(EOR)that carefully designs the data placement of replication according to the future data layout of EC to enhance the I/O efficiency of redundancy transition.ElasticMem solves the consistency problem caused by concurrent data accesses via a lightweight table-based scheme combined with data bypassing.It detects correlated read and write requests and serves subsequent read requests with local data.We implement a prototype that realizes ElasticMem based on Memcached.Experiments show that ElasticMem remarkably reduces the time of redundancy transition,the overall latency of correlated concurrent data accesses,and the latency of single data access among them.展开更多
Supercapacitors are gaining popularity due to their high cycling stability,power density,and fast charge and discharge rates.Researchers are ex-ploring electrode materials,electrolytes,and separat-ors for cost-effecti...Supercapacitors are gaining popularity due to their high cycling stability,power density,and fast charge and discharge rates.Researchers are ex-ploring electrode materials,electrolytes,and separat-ors for cost-effective energy storage systems.Ad-vances in materials science have led to the develop-ment of hybrid nanomaterials,such as combining fil-amentous carbon forms with inorganic nanoparticles,to create new charge and energy transfer processes.Notable materials for electrochemical energy-stor-age applications include MXenes,2D transition met-al carbides,and nitrides,carbon black,carbon aerogels,activated carbon,carbon nanotubes,conducting polymers,carbon fibers,and nanofibers,and graphene,because of their thermal,electrical,and mechanical properties.Carbon materials mixed with conducting polymers,ceramics,metal oxides,transition metal oxides,metal hydroxides,transition metal sulfides,trans-ition metal dichalcogenide,metal sulfides,carbides,nitrides,and biomass materials have received widespread attention due to their remarkable performance,eco-friendliness,cost-effectiveness,and renewability.This article explores the development of carbon-based hybrid materials for future supercapacitors,including electric double-layer capacitors,pseudocapacitors,and hy-brid supercapacitors.It investigates the difficulties that influence structural design,manufacturing(electrospinning,hydro-thermal/solvothermal,template-assisted synthesis,electrodeposition,electrospray,3D printing)techniques and the latest car-bon-based hybrid materials research offer practical solutions for producing high-performance,next-generation supercapacitors.展开更多
3D printing technology enhances the combustion characteristics of hybrid rocket fuels by enabling complex geometries. However, improvements in regression rates and energy properties of monotonous 3D printed fuels have...3D printing technology enhances the combustion characteristics of hybrid rocket fuels by enabling complex geometries. However, improvements in regression rates and energy properties of monotonous 3D printed fuels have been limited. This study explores the impact of poly(vinylidene fluoride) and polydopamine-coated aluminum particles on the thermal and combustion properties of 3D printed hybrid rocket fuels. Physical self-assembly and anti-solvent methods were employed for constructing composite μAl particles. Characterization using SEM, XRD, XPS, FTIR, and μCT revealed a core-shell structure and homogeneous elemental distribution. Thermal analysis showed that PVDF coatings significantly increased the heat of combustion for aluminum particles, with maximum enhancement observed in μAl@PDA@PVDF(denoted as μAl@PF) at 6.20 k J/g. Subsequently, 3D printed fuels with varying pure and composite μAl particle contents were prepared using 3D printing. Combustion tests indicated higher regression rates for Al@PF/Resin composites compared to pure resin, positively correlating with particle content. The fluorocarbon-alumina reaction during the combustion stage intensified Al particle combustion, reducing residue size. A comprehensive model based on experiments provides insights into the combustion process of PDA and PVDF-coated droplets. This study advances the design of 3D-printed hybrid rocket fuels, offering strategies to improve regression rates and energy release, crucial for enhancing solid fuel performance for hybrid propulsion.展开更多
In order to improve the quality of 3D printed raspberry preserves after post-processing,microwave ovens combining infrared and microwave methods were utilized.The effects of infrared heating temperature,infrared heati...In order to improve the quality of 3D printed raspberry preserves after post-processing,microwave ovens combining infrared and microwave methods were utilized.The effects of infrared heating temperature,infrared heating time,microwave power,microwave heating time on the center temperature,moisture content,the chroma(C*),the total color difference(ΔE*),shape fidelity,hardness,and the total anthocyanin content of 3D printed raspberry preserves were analyzed by response surface method(RSM).The results showed that under combining with the two methods,infrared heating improved the fidelity and quality degradation of printed products,while microwave heating enhanced the efficiency of infrared heating.Infrared-microwave combination cooking could maintain relatively stable color appearance and shape of 3D printed raspberry preserves.The AHP–CRITIC hybrid weighting method combined with the response surface test to determine the comprehensive weights of the evaluation indicators optimized the process parameters,and the optimal process parameters were obtained:infrared heating temperature of 190℃,infrared heating time of 10 min and 30 s,microwave power of 300 W,and microwave heating time of 2 min and 6 s.The 3D printed raspberry cooking methods obtained under the optimal conditions seldom had color variation,porous structure,uniform texture,and high shape fidelity,which retained the characteristics of personalized manufacturing by 3D printing.This study could provide a reference for the postprocessing and quality control of 3D cooking methods.展开更多
This study investigates the potential of metal additives in acrylonitrile butadiene styrene(ABS)polymer fuel to enhance hybrid rocket motor(HRM)performance through computational analysis,Chemical Equilibrium with Appl...This study investigates the potential of metal additives in acrylonitrile butadiene styrene(ABS)polymer fuel to enhance hybrid rocket motor(HRM)performance through computational analysis,Chemical Equilibrium with Applications(CEA),software.ABS was selected as the base fuel due to its thermoplastic nature,which allows for the creation of complex fuel geometries through 3D printing,offering significant flexibility in fuel design.Hybrid rockets,which combine a solid fuel with a liquid oxidiser,offer advantages in terms of operational simplicity and safety.However,conventional polymer fuels often exhibit low regression rates and suboptimal combustion efficiencies.In this research,we evaluated a range of metal additives-aluminium(Al),boron(B),nickel(Ni),copper(Cu),and iron(Fe)-at chamber pressures ranging from 1 to 30 bar and oxidiser-to-fuel(O/F)ratios between 1.1 and 12,resulting in 1800 unique test conditions.The main performance parameters used to assess each formulation were characteristic velocity(C^(*))and adiabatic flame temperature.The results revealed that each test produced a different optimum O/F ratio,with most ratios falling between 4 and 6.The highest performance was achieved at a chamber pressure of 30 bar across all formulations.Among the additives,Al and B demonstrated significant potential for improved combustion performance with increasing metal loadings.In contrast,Fe,Cu,and Ni reached optimal performance at a minimum loading of 1%.Future work includes investigating B-Al metal composites as additives into the ABS base polymer fuel,and doing experimental validation tests where the metallised ABS polymer fuel is 3D printed.展开更多
应用SYBR Green I染料能选择性结合双链DNA的特点,可检测到沙门氏菌fimI基因特异性靶序列扩增所产生的荧光信号,通过熔解曲线可知其熔点值约为85.6℃,而对其他非沙门氏菌则检测不到荧光信号。建立了一种肉品中的沙门氏菌Real-time PCR...应用SYBR Green I染料能选择性结合双链DNA的特点,可检测到沙门氏菌fimI基因特异性靶序列扩增所产生的荧光信号,通过熔解曲线可知其熔点值约为85.6℃,而对其他非沙门氏菌则检测不到荧光信号。建立了一种肉品中的沙门氏菌Real-time PCR检测方法,用该方法检测市售牛肉、香肠中的沙门氏菌,其检测灵敏度分别为13,12 cfu/25 g,从样品的处理到得出检验结果可以在10 h内完成。该检测方法具有简便、快速、特异性强、敏感度高等特点。展开更多
目的建立快速、特异性好、灵敏度高的Real-Time PCR方法定量检测沙门菌。方法根据编码沙门菌肠毒素基因stn的核苷酸序列,设计荧光探针和一对引物,通过对荧光定量PCR反应体系和反应条件的摸索,建立定量检测沙门菌的方法。结果建立的Real-...目的建立快速、特异性好、灵敏度高的Real-Time PCR方法定量检测沙门菌。方法根据编码沙门菌肠毒素基因stn的核苷酸序列,设计荧光探针和一对引物,通过对荧光定量PCR反应体系和反应条件的摸索,建立定量检测沙门菌的方法。结果建立的Real-Ti me PCR方法有很好的特异性与敏感性,所检测沙门菌结果均为阳性,而非沙门菌均为阴性;标准曲线相关系数为R2=0.993,其敏感性为5CFU。运用该方法对108份鸡粪便、50份鸡肉以及58份水样进行检测,阳性率分别为3.7%(6/108)、4%(2/50)和3.4%(2/58),与传统细菌分离检测结果相符。结论结果表明该方法具有简便、快速、特异性强、敏感性高等特点,此研究为环境及疾病诊断中沙门菌快速检测提供了新方法。展开更多
文摘Ship motions induced by waves have a significant impact on the efficiency and safety of offshore operations.Real-time prediction of ship motions in the next few seconds plays a crucial role in performing sensitive activities.However,the obvious memory effect of ship motion time series brings certain difficulty to rapid and accurate prediction.Therefore,a real-time framework based on the Long-Short Term Memory(LSTM)neural network model is proposed to predict ship motions in regular and irregular head waves.A 15000 TEU container ship model is employed to illustrate the proposed framework.The numerical implementation and the real-time ship motion prediction in irregular head waves corresponding to the different time scales are carried out based on the container ship model.The related experimental data were employed to verify the numerical simulation results.The results show that the proposed method is more robust than the classical extreme short-term prediction method based on potential flow theory in the prediction of nonlinear ship motions.
基金Project(42174170)supported by the National Natural Science Foundation of China。
文摘Controlled laboratory experiments are proved to be a valuable tool for investigating changes in underground physical properties and the related response of surface geophysical signals.The self-potential(SP)method is widely used in mineral resource exploration due to its direct correlation with underground electrochemical gradients.This paper presented the design and construction of an experimental platform based on a multi-channel SP monitoring system.The proposed platform was used to monitor the anodizing corrosion process of different metal blocks from a laboratory perspective,record the real-time SP signal generated by the redox reaction,as well as investigate the geobattery mechanism associated with the natural polarization process of metal mineral resources.The experimental results demonstrate that the constructed SP monitoring platform effectively captures time-series SP signals and provides direct laboratory evidence for the geobattery model.The measured SP data were quantitatively interpreted using the simulated annealing algorithm,and the inversion results closely match the real model.This finding highlights the potential of the SP method as a promising tool for determining the location and spatial distribution of underground polarizers.The study holds reference value for the exploration and exploitation of mineral resources in both terrestrial and marine environments.
文摘[Objective]Real-time monitoring of cow ruminant behavior is of paramount importance for promptly obtaining relevant information about cow health and predicting cow diseases.Currently,various strategies have been proposed for monitoring cow ruminant behavior,including video surveillance,sound recognition,and sensor monitoring methods.How‐ever,the application of edge device gives rise to the issue of inadequate real-time performance.To reduce the volume of data transmission and cloud computing workload while achieving real-time monitoring of dairy cow rumination behavior,a real-time monitoring method was proposed for cow ruminant behavior based on edge computing.[Methods]Autono‐mously designed edge devices were utilized to collect and process six-axis acceleration signals from cows in real-time.Based on these six-axis data,two distinct strategies,federated edge intelligence and split edge intelligence,were investigat‐ed for the real-time recognition of cow ruminant behavior.Focused on the real-time recognition method for cow ruminant behavior leveraging federated edge intelligence,the CA-MobileNet v3 network was proposed by enhancing the MobileNet v3 network with a collaborative attention mechanism.Additionally,a federated edge intelligence model was designed uti‐lizing the CA-MobileNet v3 network and the FedAvg federated aggregation algorithm.In the study on split edge intelli‐gence,a split edge intelligence model named MobileNet-LSTM was designed by integrating the MobileNet v3 network with a fusion collaborative attention mechanism and the Bi-LSTM network.[Results and Discussions]Through compara‐tive experiments with MobileNet v3 and MobileNet-LSTM,the federated edge intelligence model based on CA-Mo‐bileNet v3 achieved an average Precision rate,Recall rate,F1-Score,Specificity,and Accuracy of 97.1%,97.9%,97.5%,98.3%,and 98.2%,respectively,yielding the best recognition performance.[Conclusions]It is provided a real-time and effective method for monitoring cow ruminant behavior,and the proposed federated edge intelligence model can be ap‐plied in practical settings.
基金supported by the Fundamental Research Funds for the Central Universities(WK2150110022)Anhui Provincial Natural Science Foundation(2208085QF189)National Natural Science Foundation of China(62202440).
文摘An in-memory storage system provides submillisecond latency and improves the concurrency of user applications by caching data into memory from external storage.Fault tolerance of in-memory storage systems is essential,as the loss of cached data requires access to data from external storage,which evidently increases the response latency.Typically,replication and erasure code(EC)are two fault-tolerant schemes that pose different trade-offs between access performance and storage usage.To help make the best performance and space trade-off,we design ElasticMem,a hybrid fault-tolerant distributed in-memory storage system that supports elastic redundancy transition to dynamically change the fault-tolerant scheme.ElasticMem exploits a novel EC-oriented replication(EOR)that carefully designs the data placement of replication according to the future data layout of EC to enhance the I/O efficiency of redundancy transition.ElasticMem solves the consistency problem caused by concurrent data accesses via a lightweight table-based scheme combined with data bypassing.It detects correlated read and write requests and serves subsequent read requests with local data.We implement a prototype that realizes ElasticMem based on Memcached.Experiments show that ElasticMem remarkably reduces the time of redundancy transition,the overall latency of correlated concurrent data accesses,and the latency of single data access among them.
文摘Supercapacitors are gaining popularity due to their high cycling stability,power density,and fast charge and discharge rates.Researchers are ex-ploring electrode materials,electrolytes,and separat-ors for cost-effective energy storage systems.Ad-vances in materials science have led to the develop-ment of hybrid nanomaterials,such as combining fil-amentous carbon forms with inorganic nanoparticles,to create new charge and energy transfer processes.Notable materials for electrochemical energy-stor-age applications include MXenes,2D transition met-al carbides,and nitrides,carbon black,carbon aerogels,activated carbon,carbon nanotubes,conducting polymers,carbon fibers,and nanofibers,and graphene,because of their thermal,electrical,and mechanical properties.Carbon materials mixed with conducting polymers,ceramics,metal oxides,transition metal oxides,metal hydroxides,transition metal sulfides,trans-ition metal dichalcogenide,metal sulfides,carbides,nitrides,and biomass materials have received widespread attention due to their remarkable performance,eco-friendliness,cost-effectiveness,and renewability.This article explores the development of carbon-based hybrid materials for future supercapacitors,including electric double-layer capacitors,pseudocapacitors,and hy-brid supercapacitors.It investigates the difficulties that influence structural design,manufacturing(electrospinning,hydro-thermal/solvothermal,template-assisted synthesis,electrodeposition,electrospray,3D printing)techniques and the latest car-bon-based hybrid materials research offer practical solutions for producing high-performance,next-generation supercapacitors.
基金funded by the National Natural Science Foundation of China(Grant No.06101213)the National Natural Science Foundation of China(Grant No.22105160).
文摘3D printing technology enhances the combustion characteristics of hybrid rocket fuels by enabling complex geometries. However, improvements in regression rates and energy properties of monotonous 3D printed fuels have been limited. This study explores the impact of poly(vinylidene fluoride) and polydopamine-coated aluminum particles on the thermal and combustion properties of 3D printed hybrid rocket fuels. Physical self-assembly and anti-solvent methods were employed for constructing composite μAl particles. Characterization using SEM, XRD, XPS, FTIR, and μCT revealed a core-shell structure and homogeneous elemental distribution. Thermal analysis showed that PVDF coatings significantly increased the heat of combustion for aluminum particles, with maximum enhancement observed in μAl@PDA@PVDF(denoted as μAl@PF) at 6.20 k J/g. Subsequently, 3D printed fuels with varying pure and composite μAl particle contents were prepared using 3D printing. Combustion tests indicated higher regression rates for Al@PF/Resin composites compared to pure resin, positively correlating with particle content. The fluorocarbon-alumina reaction during the combustion stage intensified Al particle combustion, reducing residue size. A comprehensive model based on experiments provides insights into the combustion process of PDA and PVDF-coated droplets. This study advances the design of 3D-printed hybrid rocket fuels, offering strategies to improve regression rates and energy release, crucial for enhancing solid fuel performance for hybrid propulsion.
基金Supported by the National Natural Science Foundation of China(32072352)。
文摘In order to improve the quality of 3D printed raspberry preserves after post-processing,microwave ovens combining infrared and microwave methods were utilized.The effects of infrared heating temperature,infrared heating time,microwave power,microwave heating time on the center temperature,moisture content,the chroma(C*),the total color difference(ΔE*),shape fidelity,hardness,and the total anthocyanin content of 3D printed raspberry preserves were analyzed by response surface method(RSM).The results showed that under combining with the two methods,infrared heating improved the fidelity and quality degradation of printed products,while microwave heating enhanced the efficiency of infrared heating.Infrared-microwave combination cooking could maintain relatively stable color appearance and shape of 3D printed raspberry preserves.The AHP–CRITIC hybrid weighting method combined with the response surface test to determine the comprehensive weights of the evaluation indicators optimized the process parameters,and the optimal process parameters were obtained:infrared heating temperature of 190℃,infrared heating time of 10 min and 30 s,microwave power of 300 W,and microwave heating time of 2 min and 6 s.The 3D printed raspberry cooking methods obtained under the optimal conditions seldom had color variation,porous structure,uniform texture,and high shape fidelity,which retained the characteristics of personalized manufacturing by 3D printing.This study could provide a reference for the postprocessing and quality control of 3D cooking methods.
文摘This study investigates the potential of metal additives in acrylonitrile butadiene styrene(ABS)polymer fuel to enhance hybrid rocket motor(HRM)performance through computational analysis,Chemical Equilibrium with Applications(CEA),software.ABS was selected as the base fuel due to its thermoplastic nature,which allows for the creation of complex fuel geometries through 3D printing,offering significant flexibility in fuel design.Hybrid rockets,which combine a solid fuel with a liquid oxidiser,offer advantages in terms of operational simplicity and safety.However,conventional polymer fuels often exhibit low regression rates and suboptimal combustion efficiencies.In this research,we evaluated a range of metal additives-aluminium(Al),boron(B),nickel(Ni),copper(Cu),and iron(Fe)-at chamber pressures ranging from 1 to 30 bar and oxidiser-to-fuel(O/F)ratios between 1.1 and 12,resulting in 1800 unique test conditions.The main performance parameters used to assess each formulation were characteristic velocity(C^(*))and adiabatic flame temperature.The results revealed that each test produced a different optimum O/F ratio,with most ratios falling between 4 and 6.The highest performance was achieved at a chamber pressure of 30 bar across all formulations.Among the additives,Al and B demonstrated significant potential for improved combustion performance with increasing metal loadings.In contrast,Fe,Cu,and Ni reached optimal performance at a minimum loading of 1%.Future work includes investigating B-Al metal composites as additives into the ABS base polymer fuel,and doing experimental validation tests where the metallised ABS polymer fuel is 3D printed.
文摘目的建立快速、特异性好、灵敏度高的Real-Time PCR方法定量检测沙门菌。方法根据编码沙门菌肠毒素基因stn的核苷酸序列,设计荧光探针和一对引物,通过对荧光定量PCR反应体系和反应条件的摸索,建立定量检测沙门菌的方法。结果建立的Real-Ti me PCR方法有很好的特异性与敏感性,所检测沙门菌结果均为阳性,而非沙门菌均为阴性;标准曲线相关系数为R2=0.993,其敏感性为5CFU。运用该方法对108份鸡粪便、50份鸡肉以及58份水样进行检测,阳性率分别为3.7%(6/108)、4%(2/50)和3.4%(2/58),与传统细菌分离检测结果相符。结论结果表明该方法具有简便、快速、特异性强、敏感性高等特点,此研究为环境及疾病诊断中沙门菌快速检测提供了新方法。
