ASEAN’s major power balancing strategy refers to the balancing strategy adopted by ASEAN and its member states to seek national and regional security and development by maintaining multi-faceted friendship and impart...ASEAN’s major power balancing strategy refers to the balancing strategy adopted by ASEAN and its member states to seek national and regional security and development by maintaining multi-faceted friendship and impartiality with surrounding major powers.The evolution of this strategy is a process of dynamic adjustment,with ASEAN and its members being the implementing subjects,major powers the objects.展开更多
Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition d...Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition degree can easily be adjusted simultaneously.This paper introduces a new type of pliable FR codes,called absolute balanced pliable FR(ABPFR)codes,in which the access balancing in DSS is considered.Additionally,the equivalence between pliable FR codes and resolvable transversal packings in combinatorial design theory is presented.Then constructions of pliable FR codes and ABPFR codes based on resolvable transversal packings are presented.展开更多
The existence of the aeroengine casing,limited monitoring points,and multi-fault characteristics make obtaining the rotor’s vibration transmission characteristics challenging,resulting in difficulties accurately iden...The existence of the aeroengine casing,limited monitoring points,and multi-fault characteristics make obtaining the rotor’s vibration transmission characteristics challenging,resulting in difficulties accurately identifying the rotor unbalance.This paper utilizes a high-frequency composite sensor to monitor the engine’s blade tip clearance(BTC)and extracts unbalanced information from BTC signals for rotor dynamic balancing,while avoiding the need for the once per revolution(OPR)sensor.First,the vibration characteristics of the rotor-blade system under multi-fault conditions are investigated.Then,based on BTC measurement,a none OPR method and an unbalance identification method are proposed,in which the radial vibration of the blade tip in the BTC signals at different speeds is extracted and operated in the time domain to obtain the rotor unbalanced vibration,the signal is reconstructed,and cross-correlation analysis is used to accurately identify the magnitude and phase of the unbalanced signal.Finally,a rotor test bench is utilized for experimental verification.The results reveal that the dynamic balancing method based on the BTC signal can more precisely identify the rotor unbalance than the traditional rotor dynamic balancing method.The application of this technique will effectively improve engine health management and fault prediction.展开更多
That herbs with the"hot"property used to treat"cold"syndromes is a guiding principle of clinical prescription and medication in traditional Chinese medicine(TCM).However,this theory of TCM is still...That herbs with the"hot"property used to treat"cold"syndromes is a guiding principle of clinical prescription and medication in traditional Chinese medicine(TCM).However,this theory of TCM is still in the‘black box'stage,and few in-depth studies have examined the biological mechanisms underpinning the hot properties of herbs.展开更多
In recent years,load balancing routing al-gorithms have been extensively studied in satellite net-works.Most existing studies focus on path selection and hop-count optimization for end-to-end transmis-sion,while overl...In recent years,load balancing routing al-gorithms have been extensively studied in satellite net-works.Most existing studies focus on path selection and hop-count optimization for end-to-end transmis-sion,while overlooking congestion issues on feeder links caused by the limited number and centralized distribution of ground stations.Hence,a multi-service routing algorithm called the Multi-service Load Bal-ancing Routing Algorithm for Traffic Return(MLB-TR)is proposed.Unlike traditional approaches,MLB-TR aims to achieve a broader and more comprehensive load balancing objective.Specifically,based on the service type,an appropriate landing satellite is first selected by considering factors such as shortest path hop count and satellite load.Then,a set of candidate paths from the source satellite to the selected landing satellite is computed.Finally,using the regional load balancing index as the optimization objective,the final transmission path is selected from the candidate path set.Simulation results show that the proposed algo-rithm outperforms the existing works.展开更多
In deep drilling applications,such as those for geothermal energy,there are many challenges,such as those related to efficient operation of the drilling fluid(mud)pumping system.Legacy drilling rigs often use paired,p...In deep drilling applications,such as those for geothermal energy,there are many challenges,such as those related to efficient operation of the drilling fluid(mud)pumping system.Legacy drilling rigs often use paired,parallel-connected independent-excitation direct-current(DC)motors for mud pumps,that are supplied by a single power converter.This configuration results in electrical power imbalance,thus reducing its efficiency.This paper investigates this power imbalance issue in such legacy DC mud pump drive systems and offers an innovative solution in the form of a closed-loop control system for electrical load balancing.The paper first analyzes the drilling fluid circulation and electrical drive layout to develop an analytical model that can be used for electrical load balancing and related energy efficiency improvements.Based on this analysis,a feedback control system(so-called“current mirror”control system)is designed to balance the electrical load(i.e.,armature currents)of parallel-connected DC machines by adjusting the excitation current of one of the DC machines,thus mitigating the power imbalance of the electrical drive.Theproposed control systemeffectiveness has been validated,first through simulations,followed by experimental testing on a deep drilling rig during commissioning and field tests.The results demonstrate the practical viability of the proposed“current mirror”control system that can effectively and rather quickly equalize the armature currents of both DC machines in a parallel-connected electrical drive,and thus balance both the electrical and mechanical load of individual DC machines under realistic operating conditions of the mud pump electrical drive.展开更多
The uncertain nature of mapping user tasks to Virtual Machines(VMs) causes system failure or execution delay in Cloud Computing.To maximize cloud resource throughput and decrease user response time,load balancing is n...The uncertain nature of mapping user tasks to Virtual Machines(VMs) causes system failure or execution delay in Cloud Computing.To maximize cloud resource throughput and decrease user response time,load balancing is needed.Possible load balancing is needed to overcome user task execution delay and system failure.Most swarm intelligent dynamic load balancing solutions that used hybrid metaheuristic algorithms failed to balance exploitation and exploration.Most load balancing methods were insufficient to handle the growing uncertainty in job distribution to VMs.Thus,the Hybrid Spotted Hyena and Whale Optimization Algorithm-based Dynamic Load Balancing Mechanism(HSHWOA) partitions traffic among numerous VMs or servers to guarantee user chores are completed quickly.This load balancing approach improved performance by considering average network latency,dependability,and throughput.This hybridization of SHOA and WOA aims to improve the trade-off between exploration and exploitation,assign jobs to VMs with more solution diversity,and prevent the solution from reaching a local optimality.Pysim-based experimental verification and testing for the proposed HSHWOA showed a 12.38% improvement in minimized makespan,16.21% increase in mean throughput,and 14.84% increase in network stability compared to baseline load balancing strategies like Fractional Improved Whale Social Optimization Based VM Migration Strategy FIWSOA,HDWOA,and Binary Bird Swap.展开更多
In low Earth orbit(LEO)satellite networks,on-board energy resources of each satellite are extremely limited.And with the increase of the node number and the traffic transmis-sion pressure,the energy consumption in the...In low Earth orbit(LEO)satellite networks,on-board energy resources of each satellite are extremely limited.And with the increase of the node number and the traffic transmis-sion pressure,the energy consumption in the networks presents uneven distribution.To achieve energy balance in networks,an energy consumption balancing optimization algorithm of LEO networks based on distance energy factor(DEF)is proposed.The DEF is defined as the function of the inter-satellite link dis-tance and the cumulative network energy consumption ratio.According to the minimum sum of DEF on inter-satellite links,an energy consumption balancing algorithm based on DEF is pro-posed,which can realize dynamic traffic transmission optimiza-tion of multiple traffic services.It can effectively reduce the energy consumption pressure of core nodes with high energy consumption in the network,make full use of idle nodes with low energy consumption,and optimize the energy consumption dis-tribution of the whole network according to the continuous itera-tions of each traffic service flow.Simulation results show that,compared with the traditional shortest path algorithm,the pro-posed method can improve the balancing performance of nodes by 75%under certain traffic pressure,and realize the optimiza-tion of energy consumption balancing of the whole network.展开更多
In response to the deficiencies of commonly used optimization methods for assembly lines,a production demand-oriented optimization method for assembly lines is proposed.Taking a certain compressor assembly line as an ...In response to the deficiencies of commonly used optimization methods for assembly lines,a production demand-oriented optimization method for assembly lines is proposed.Taking a certain compressor assembly line as an example,the production rhythm and the number of workstations are calculated based on production requirements and working systems.With assembly rhythm and smoothing index as optimization goals,an improved particle swarm optimization algorithm is employed for process allocation.Subsequently,Flexsim simulation is used to analyze the assembly line.The final results show that after optimization using the improved particle swarm algorithm,the assembly line balance rate increased from 71.1%to 85.9%,and the assembly line smoothing index decreased from 47.4 to 29.8,significantly enhancing assembly efficiency.This demonstrates the effectiveness of the proposed optimization method for the assembly line and provides a reference for other products in the same industry.展开更多
Cascaded H-bridge inverter(CHBI) with supercapacitors(SCs) and dc-dc stage shows significant promise for medium to high voltage energy storage applications. This paper investigates the voltage balance of capacitors wi...Cascaded H-bridge inverter(CHBI) with supercapacitors(SCs) and dc-dc stage shows significant promise for medium to high voltage energy storage applications. This paper investigates the voltage balance of capacitors within the CHBI, including both the dc-link capacitors and SCs. Balance control over the dc-link capacitor voltages is realized by the dcdc stage in each submodule(SM), while a hybrid modulation strategy(HMS) is implemented in the H-bridge to balance the SC voltages among the SMs. Meanwhile, the dc-link voltage fluctuations are analyzed under the HMS. A virtual voltage variable is introduced to coordinate the balancing of dc-link capacitor voltages and SC voltages. Compared to the balancing method that solely considers the SC voltages, the presented method reduces the dc-link voltage fluctuations without affecting the voltage balance of SCs. Finally, both simulation and experimental results verify the effectiveness of the presented method.展开更多
Small and isolated populations face several intrinsic risks,such as genetic drift,inbreeding depression,and reduced gene fow.Thus,patterns of genetic diversity and differentiation have become an important focus of con...Small and isolated populations face several intrinsic risks,such as genetic drift,inbreeding depression,and reduced gene fow.Thus,patterns of genetic diversity and differentiation have become an important focus of conservation genetics research.The golden snub-nosed monkey Rhinopithecus roxellana,an endangered species endemic to China,has experienced rapid reduction in population size and severe population fragmentation over the past few decades.We measured the patterns of genetic diversity and population differentiation using both neutral microsatellites and adaptive major histocompatibility complex(MHC)genes in 2 R.roxellana populations(DPY and GNG)distributed on the northern and southern slopes of the Qinling Mountains,respectively.Eight MHC-linked haplotypes formed by 5 DQA1 alleles,5 DQB1 alleles,5 DRB1 alleles,and 4 DRB2 alleles were detected in the 2 populations.The larger GNG population showed higher genetic variation for both MHC and microsatellites than the smaller DPY population,suggesting an effect of genetic drift on genetic variation.Genetic differentiation index(FST)outlier analyses,principal coordinate analysis(PCoA),and inferred population genetic structure showed lower genetic differentiation in the MHC variations than microsatellites,suggesting that pathogen-mediated balancing selection,rather than local adaptation,homogenized the MHC genes of both populations.This study indicates that both balancing selection and genetic drift may shape genetic variation and differentiation in small and fragmented populations.展开更多
This paper focuses on the scheduling problem of workflow tasks that exhibit interdependencies.Unlike indepen-dent batch tasks,workflows typically consist of multiple subtasks with intrinsic correlations and dependenci...This paper focuses on the scheduling problem of workflow tasks that exhibit interdependencies.Unlike indepen-dent batch tasks,workflows typically consist of multiple subtasks with intrinsic correlations and dependencies.It necessitates the distribution of various computational tasks to appropriate computing node resources in accor-dance with task dependencies to ensure the smooth completion of the entire workflow.Workflow scheduling must consider an array of factors,including task dependencies,availability of computational resources,and the schedulability of tasks.Therefore,this paper delves into the distributed graph database workflow task scheduling problem and proposes a workflow scheduling methodology based on deep reinforcement learning(DRL).The method optimizes the maximum completion time(makespan)and response time of workflow tasks,aiming to enhance the responsiveness of workflow tasks while ensuring the minimization of the makespan.The experimental results indicate that the Q-learning Deep Reinforcement Learning(Q-DRL)algorithm markedly diminishes the makespan and refines the average response time within distributed graph database environments.In quantifying makespan,Q-DRL achieves mean reductions of 12.4%and 11.9%over established First-fit and Random scheduling strategies,respectively.Additionally,Q-DRL surpasses the performance of both DRL-Cloud and Improved Deep Q-learning Network(IDQN)algorithms,with improvements standing at 4.4%and 2.6%,respectively.With reference to average response time,the Q-DRL approach exhibits a significantly enhanced performance in the scheduling of workflow tasks,decreasing the average by 2.27%and 4.71%when compared to IDQN and DRL-Cloud,respectively.The Q-DRL algorithm also demonstrates a notable increase in the efficiency of system resource utilization,reducing the average idle rate by 5.02%and 9.30%in comparison to IDQN and DRL-Cloud,respectively.These findings support the assertion that Q-DRL not only upholds a lower average idle rate but also effectively curtails the average response time,thereby substantially improving processing efficiency and optimizing resource utilization within distributed graph database systems.展开更多
This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassemb...This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle time.Based on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is designed.To enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular individuals.The established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,respectively.Introducing a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.展开更多
This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)f...This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.展开更多
Cloud Computing has the ability to provide on-demand access to a shared resource pool.It has completely changed the way businesses are managed,implement applications,and provide services.The rise in popularity has led...Cloud Computing has the ability to provide on-demand access to a shared resource pool.It has completely changed the way businesses are managed,implement applications,and provide services.The rise in popularity has led to a significant increase in the user demand for services.However,in cloud environments efficient load balancing is essential to ensure optimal performance and resource utilization.This systematic review targets a detailed description of load balancing techniques including static and dynamic load balancing algorithms.Specifically,metaheuristic-based dynamic load balancing algorithms are identified as the optimal solution in case of increased traffic.In a cloud-based context,this paper describes load balancing measurements,including the benefits and drawbacks associated with the selected load balancing techniques.It also summarizes the algorithms based on implementation,time complexity,adaptability,associated issue(s),and targeted QoS parameters.Additionally,the analysis evaluates the tools and instruments utilized in each investigated study.Moreover,comparative analysis among static,traditional dynamic and metaheuristic algorithms based on response time by using the CloudSim simulation tool is also performed.Finally,the key open problems and potential directions for the state-of-the-art metaheuristic-based approaches are also addressed.展开更多
With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people’s needs. The...With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people’s needs. The development of software defined networks has brought new opportunities and challenges to future networks. The data and control separation characteristics of SDN improve the performance of the entire network. Researchers have integrated SDN architecture into data centers to improve network resource utilization and performance. This paper first introduces the basic concepts of SDN and data center networks. Then it discusses SDN-based load balancing mechanisms for data centers from different perspectives. Finally, it summarizes and looks forward to the study on SDN-based load balancing mechanisms and its development trend.展开更多
In this paper, a sender-initiated protocol is applied which uses fuzzy logic control method to improve computer networks performance by balancing loads among computers. This new model devises sender-initiated protocol...In this paper, a sender-initiated protocol is applied which uses fuzzy logic control method to improve computer networks performance by balancing loads among computers. This new model devises sender-initiated protocol for load transfer for load balancing. Groups are formed and every group has a node called a designated representative (DR). During load transferring processes, loads are transferred using the DR in each group to achieve load balancing purposes. The simulation results show that the performance of the protocol proposed is better than the compared conventional method. This protocol is more stable than the method without using the fuzzy logic control.展开更多
Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency.To tackle this problem,we propose an Unmanned Aerial Vehicle(UAV)-assisted wireless network in which the UAV ...Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency.To tackle this problem,we propose an Unmanned Aerial Vehicle(UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its adjacent underloaded cell.To fully exploit its potential,we jointly optimize the UAV position,user association,spectrum allocation,and power allocation to maximize the sum-log-rate of all users in two adjacent cells.To tackle the complicated joint optimization problem,we first design a genetic-based algorithm to optimize the UAV position.Then,we simplify the problem by theoretical analysis and devise a low-complexity algorithm according to the branch-and-bound method,so as to obtain the optimal user association and spectrum allocation schemes.We further propose an iterative power allocation algorithm based on the sequential convex approximation theory.The simulation results indicate that the proposed UAV-assisted wireless network is superior to the terrestrial network in both utility and throughput,and the proposed algorithms can substantially improve the network performance in comparison with the other schemes.展开更多
The human scalp harbors a diverse range of microbiome,much like other skin surfaces,where both beneficial and harmful microorganisms coexist.This study explores the possibility of balancing key scalp microorganisms,pa...The human scalp harbors a diverse range of microbiome,much like other skin surfaces,where both beneficial and harmful microorganisms coexist.This study explores the possibility of balancing key scalp microorganisms,particularly Staphylococcus epidermidis,Staphylococcus aureus and Malassezia species.While Staphylococcus epidermidis plays a beneficial role in maintaining scalp health by producing antimicrobial proteins and supporting the skin barrier,Staphylococcus aureus is identified as a pathogen linked to skin infections and dandruff formation.Malassezia fungi degrade triglycerides in sebum into unsaturated fatty acids,exacerbating scalp conditions like dandruff.In order to promote the beneficial microbe while inhibit the harmful ones,we investigated the combination of 1.0 mM pyrrolidone carboxylate-zinc(PCA-Zn),0.2%malt oligosaccharides(MT:corn-derived oligosaccharide mainly containing maltotetraose)and 0.05 mM Hinokitiol on its microbial activity,which significantly enhanced the growth of Staphylococcus epidermidis while inhibiting both Staphylococcus aureus and Malassezia,offering insights into promising strategies for scalp care.展开更多
Imbalance vibration is a typical failure mode of rotational machines and has significant negative effects on the efficiency,accuracy,and service life of equipment.To automatically reduce the imbalance vibration during...Imbalance vibration is a typical failure mode of rotational machines and has significant negative effects on the efficiency,accuracy,and service life of equipment.To automatically reduce the imbalance vibration during the operational process,different types of active balancing actuators have been designed and widely applied in actual production.However,the existing electromagnetic-ring active balancing actuator is designed based on an axial excitation structure which can cause structural instability and has low electromagnetic driving efficiency.In this paper,a novel radial excitation structure and the working principle of an electromagnetic-ring active balancing actuator with a combined driving strategy are presented in detail.Then,based on a finite element model,the performance parameters of the actuator are analyzed,and reasonable design parameters are obtained.Self-locking torque measurements and comparative static and dynamic experiments are performed to validate the self-locking torque and driving efficiency of the actuator.The results indicate that this novel active balancing actuator has sufficient self-locking torque,achieves normal step rotation at 2000 r/min,and reduces the driving voltage by 12.5%.The proposed novel balancing actuator using radial excitation and a combination of permanent magnets and soft-iron blocks has improved electromagnetic efficiency and a more stable and compact structure.展开更多
文摘ASEAN’s major power balancing strategy refers to the balancing strategy adopted by ASEAN and its member states to seek national and regional security and development by maintaining multi-faceted friendship and impartiality with surrounding major powers.The evolution of this strategy is a process of dynamic adjustment,with ASEAN and its members being the implementing subjects,major powers the objects.
基金Supported in part by the National Key R&D Program of China(No.2020YFA0712300)NSFC(No.61872353)。
文摘Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition degree can easily be adjusted simultaneously.This paper introduces a new type of pliable FR codes,called absolute balanced pliable FR(ABPFR)codes,in which the access balancing in DSS is considered.Additionally,the equivalence between pliable FR codes and resolvable transversal packings in combinatorial design theory is presented.Then constructions of pliable FR codes and ABPFR codes based on resolvable transversal packings are presented.
基金supported by the Key Program of National Natural Science Foundation of China(No.92160203)National Natural Science Foundation of China(No.92360306).
文摘The existence of the aeroengine casing,limited monitoring points,and multi-fault characteristics make obtaining the rotor’s vibration transmission characteristics challenging,resulting in difficulties accurately identifying the rotor unbalance.This paper utilizes a high-frequency composite sensor to monitor the engine’s blade tip clearance(BTC)and extracts unbalanced information from BTC signals for rotor dynamic balancing,while avoiding the need for the once per revolution(OPR)sensor.First,the vibration characteristics of the rotor-blade system under multi-fault conditions are investigated.Then,based on BTC measurement,a none OPR method and an unbalance identification method are proposed,in which the radial vibration of the blade tip in the BTC signals at different speeds is extracted and operated in the time domain to obtain the rotor unbalanced vibration,the signal is reconstructed,and cross-correlation analysis is used to accurately identify the magnitude and phase of the unbalanced signal.Finally,a rotor test bench is utilized for experimental verification.The results reveal that the dynamic balancing method based on the BTC signal can more precisely identify the rotor unbalance than the traditional rotor dynamic balancing method.The application of this technique will effectively improve engine health management and fault prediction.
基金supported by the Chief Scientist of Qi-Huang Project of the National Traditional Chinese Medicine Inheritance and Innovation“One Hundred Million”Talent Project,China(Grant No.:[2021]No.7)the National Famous Old Traditional Chinese Medicine Experts Inheritance Studio Construction Program of National Administration of Traditional Chinese Medicine,China(Grant No.:[2022]No.75)+3 种基金the Seventh Batch of National Famous Old Traditional Chinese Medicine Experts Experience Heritage Construction Program of National Administration of Traditional Chinese Medicine,China(Grant No.:[2022]No.76)Heilongjiang Touyan Innovation Team Program,China(Grant No.:[2019]No.5)the Natural Science Foundation of Zhejiang Province(Grant No.:LQN25H280009)the Research Project of Zhejiang Chinese Medical University,China(Grant No.:2023RCZXZK22).
文摘That herbs with the"hot"property used to treat"cold"syndromes is a guiding principle of clinical prescription and medication in traditional Chinese medicine(TCM).However,this theory of TCM is still in the‘black box'stage,and few in-depth studies have examined the biological mechanisms underpinning the hot properties of herbs.
基金supported by the National Key Research and Development Program of China under Grant No.2022YFB2902501the Fundamental Research Funds for the Central Universities under Grant No.2023ZCJH09the Haidian District Golden Bridge Seed Fund of Beijing Municipality under Grant No.S2024161.
文摘In recent years,load balancing routing al-gorithms have been extensively studied in satellite net-works.Most existing studies focus on path selection and hop-count optimization for end-to-end transmis-sion,while overlooking congestion issues on feeder links caused by the limited number and centralized distribution of ground stations.Hence,a multi-service routing algorithm called the Multi-service Load Bal-ancing Routing Algorithm for Traffic Return(MLB-TR)is proposed.Unlike traditional approaches,MLB-TR aims to achieve a broader and more comprehensive load balancing objective.Specifically,based on the service type,an appropriate landing satellite is first selected by considering factors such as shortest path hop count and satellite load.Then,a set of candidate paths from the source satellite to the selected landing satellite is computed.Finally,using the regional load balancing index as the optimization objective,the final transmission path is selected from the candidate path set.Simulation results show that the proposed algo-rithm outperforms the existing works.
文摘In deep drilling applications,such as those for geothermal energy,there are many challenges,such as those related to efficient operation of the drilling fluid(mud)pumping system.Legacy drilling rigs often use paired,parallel-connected independent-excitation direct-current(DC)motors for mud pumps,that are supplied by a single power converter.This configuration results in electrical power imbalance,thus reducing its efficiency.This paper investigates this power imbalance issue in such legacy DC mud pump drive systems and offers an innovative solution in the form of a closed-loop control system for electrical load balancing.The paper first analyzes the drilling fluid circulation and electrical drive layout to develop an analytical model that can be used for electrical load balancing and related energy efficiency improvements.Based on this analysis,a feedback control system(so-called“current mirror”control system)is designed to balance the electrical load(i.e.,armature currents)of parallel-connected DC machines by adjusting the excitation current of one of the DC machines,thus mitigating the power imbalance of the electrical drive.Theproposed control systemeffectiveness has been validated,first through simulations,followed by experimental testing on a deep drilling rig during commissioning and field tests.The results demonstrate the practical viability of the proposed“current mirror”control system that can effectively and rather quickly equalize the armature currents of both DC machines in a parallel-connected electrical drive,and thus balance both the electrical and mechanical load of individual DC machines under realistic operating conditions of the mud pump electrical drive.
文摘The uncertain nature of mapping user tasks to Virtual Machines(VMs) causes system failure or execution delay in Cloud Computing.To maximize cloud resource throughput and decrease user response time,load balancing is needed.Possible load balancing is needed to overcome user task execution delay and system failure.Most swarm intelligent dynamic load balancing solutions that used hybrid metaheuristic algorithms failed to balance exploitation and exploration.Most load balancing methods were insufficient to handle the growing uncertainty in job distribution to VMs.Thus,the Hybrid Spotted Hyena and Whale Optimization Algorithm-based Dynamic Load Balancing Mechanism(HSHWOA) partitions traffic among numerous VMs or servers to guarantee user chores are completed quickly.This load balancing approach improved performance by considering average network latency,dependability,and throughput.This hybridization of SHOA and WOA aims to improve the trade-off between exploration and exploitation,assign jobs to VMs with more solution diversity,and prevent the solution from reaching a local optimality.Pysim-based experimental verification and testing for the proposed HSHWOA showed a 12.38% improvement in minimized makespan,16.21% increase in mean throughput,and 14.84% increase in network stability compared to baseline load balancing strategies like Fractional Improved Whale Social Optimization Based VM Migration Strategy FIWSOA,HDWOA,and Binary Bird Swap.
基金supported by the National Key Research and Development Program(2021YFB2900604).
文摘In low Earth orbit(LEO)satellite networks,on-board energy resources of each satellite are extremely limited.And with the increase of the node number and the traffic transmis-sion pressure,the energy consumption in the networks presents uneven distribution.To achieve energy balance in networks,an energy consumption balancing optimization algorithm of LEO networks based on distance energy factor(DEF)is proposed.The DEF is defined as the function of the inter-satellite link dis-tance and the cumulative network energy consumption ratio.According to the minimum sum of DEF on inter-satellite links,an energy consumption balancing algorithm based on DEF is pro-posed,which can realize dynamic traffic transmission optimiza-tion of multiple traffic services.It can effectively reduce the energy consumption pressure of core nodes with high energy consumption in the network,make full use of idle nodes with low energy consumption,and optimize the energy consumption dis-tribution of the whole network according to the continuous itera-tions of each traffic service flow.Simulation results show that,compared with the traditional shortest path algorithm,the pro-posed method can improve the balancing performance of nodes by 75%under certain traffic pressure,and realize the optimiza-tion of energy consumption balancing of the whole network.
文摘In response to the deficiencies of commonly used optimization methods for assembly lines,a production demand-oriented optimization method for assembly lines is proposed.Taking a certain compressor assembly line as an example,the production rhythm and the number of workstations are calculated based on production requirements and working systems.With assembly rhythm and smoothing index as optimization goals,an improved particle swarm optimization algorithm is employed for process allocation.Subsequently,Flexsim simulation is used to analyze the assembly line.The final results show that after optimization using the improved particle swarm algorithm,the assembly line balance rate increased from 71.1%to 85.9%,and the assembly line smoothing index decreased from 47.4 to 29.8,significantly enhancing assembly efficiency.This demonstrates the effectiveness of the proposed optimization method for the assembly line and provides a reference for other products in the same industry.
基金supported in part by the CAS Project for Young Scientists in Basic Research under Grant No. YSBR-045the Youth Innovation Promotion Association CAS under Grant 2022137the Institute of Electrical Engineering CAS under Grant E155320101。
文摘Cascaded H-bridge inverter(CHBI) with supercapacitors(SCs) and dc-dc stage shows significant promise for medium to high voltage energy storage applications. This paper investigates the voltage balance of capacitors within the CHBI, including both the dc-link capacitors and SCs. Balance control over the dc-link capacitor voltages is realized by the dcdc stage in each submodule(SM), while a hybrid modulation strategy(HMS) is implemented in the H-bridge to balance the SC voltages among the SMs. Meanwhile, the dc-link voltage fluctuations are analyzed under the HMS. A virtual voltage variable is introduced to coordinate the balancing of dc-link capacitor voltages and SC voltages. Compared to the balancing method that solely considers the SC voltages, the presented method reduces the dc-link voltage fluctuations without affecting the voltage balance of SCs. Finally, both simulation and experimental results verify the effectiveness of the presented method.
基金funded by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB31020302)the National Natural Science Foundation of China(31730104,31770425,32071495,32170515,32070453,and 32000317)Derek W.Dunn was supported by a Shaanxi Province Talents 100 Fellowships.
文摘Small and isolated populations face several intrinsic risks,such as genetic drift,inbreeding depression,and reduced gene fow.Thus,patterns of genetic diversity and differentiation have become an important focus of conservation genetics research.The golden snub-nosed monkey Rhinopithecus roxellana,an endangered species endemic to China,has experienced rapid reduction in population size and severe population fragmentation over the past few decades.We measured the patterns of genetic diversity and population differentiation using both neutral microsatellites and adaptive major histocompatibility complex(MHC)genes in 2 R.roxellana populations(DPY and GNG)distributed on the northern and southern slopes of the Qinling Mountains,respectively.Eight MHC-linked haplotypes formed by 5 DQA1 alleles,5 DQB1 alleles,5 DRB1 alleles,and 4 DRB2 alleles were detected in the 2 populations.The larger GNG population showed higher genetic variation for both MHC and microsatellites than the smaller DPY population,suggesting an effect of genetic drift on genetic variation.Genetic differentiation index(FST)outlier analyses,principal coordinate analysis(PCoA),and inferred population genetic structure showed lower genetic differentiation in the MHC variations than microsatellites,suggesting that pathogen-mediated balancing selection,rather than local adaptation,homogenized the MHC genes of both populations.This study indicates that both balancing selection and genetic drift may shape genetic variation and differentiation in small and fragmented populations.
基金funded by the Science and Technology Foundation of State Grid Corporation of China(Grant No.5108-202218280A-2-397-XG).
文摘This paper focuses on the scheduling problem of workflow tasks that exhibit interdependencies.Unlike indepen-dent batch tasks,workflows typically consist of multiple subtasks with intrinsic correlations and dependencies.It necessitates the distribution of various computational tasks to appropriate computing node resources in accor-dance with task dependencies to ensure the smooth completion of the entire workflow.Workflow scheduling must consider an array of factors,including task dependencies,availability of computational resources,and the schedulability of tasks.Therefore,this paper delves into the distributed graph database workflow task scheduling problem and proposes a workflow scheduling methodology based on deep reinforcement learning(DRL).The method optimizes the maximum completion time(makespan)and response time of workflow tasks,aiming to enhance the responsiveness of workflow tasks while ensuring the minimization of the makespan.The experimental results indicate that the Q-learning Deep Reinforcement Learning(Q-DRL)algorithm markedly diminishes the makespan and refines the average response time within distributed graph database environments.In quantifying makespan,Q-DRL achieves mean reductions of 12.4%and 11.9%over established First-fit and Random scheduling strategies,respectively.Additionally,Q-DRL surpasses the performance of both DRL-Cloud and Improved Deep Q-learning Network(IDQN)algorithms,with improvements standing at 4.4%and 2.6%,respectively.With reference to average response time,the Q-DRL approach exhibits a significantly enhanced performance in the scheduling of workflow tasks,decreasing the average by 2.27%and 4.71%when compared to IDQN and DRL-Cloud,respectively.The Q-DRL algorithm also demonstrates a notable increase in the efficiency of system resource utilization,reducing the average idle rate by 5.02%and 9.30%in comparison to IDQN and DRL-Cloud,respectively.These findings support the assertion that Q-DRL not only upholds a lower average idle rate but also effectively curtails the average response time,thereby substantially improving processing efficiency and optimizing resource utilization within distributed graph database systems.
文摘This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle time.Based on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is designed.To enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular individuals.The established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,respectively.Introducing a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.
文摘This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.
文摘Cloud Computing has the ability to provide on-demand access to a shared resource pool.It has completely changed the way businesses are managed,implement applications,and provide services.The rise in popularity has led to a significant increase in the user demand for services.However,in cloud environments efficient load balancing is essential to ensure optimal performance and resource utilization.This systematic review targets a detailed description of load balancing techniques including static and dynamic load balancing algorithms.Specifically,metaheuristic-based dynamic load balancing algorithms are identified as the optimal solution in case of increased traffic.In a cloud-based context,this paper describes load balancing measurements,including the benefits and drawbacks associated with the selected load balancing techniques.It also summarizes the algorithms based on implementation,time complexity,adaptability,associated issue(s),and targeted QoS parameters.Additionally,the analysis evaluates the tools and instruments utilized in each investigated study.Moreover,comparative analysis among static,traditional dynamic and metaheuristic algorithms based on response time by using the CloudSim simulation tool is also performed.Finally,the key open problems and potential directions for the state-of-the-art metaheuristic-based approaches are also addressed.
文摘With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people’s needs. The development of software defined networks has brought new opportunities and challenges to future networks. The data and control separation characteristics of SDN improve the performance of the entire network. Researchers have integrated SDN architecture into data centers to improve network resource utilization and performance. This paper first introduces the basic concepts of SDN and data center networks. Then it discusses SDN-based load balancing mechanisms for data centers from different perspectives. Finally, it summarizes and looks forward to the study on SDN-based load balancing mechanisms and its development trend.
文摘In this paper, a sender-initiated protocol is applied which uses fuzzy logic control method to improve computer networks performance by balancing loads among computers. This new model devises sender-initiated protocol for load transfer for load balancing. Groups are formed and every group has a node called a designated representative (DR). During load transferring processes, loads are transferred using the DR in each group to achieve load balancing purposes. The simulation results show that the performance of the protocol proposed is better than the compared conventional method. This protocol is more stable than the method without using the fuzzy logic control.
基金supported in part by the National Key Research and Development Program of China under Grant 2020YFB1807003in part by the National Natural Science Foundation of China under Grants 61901381,62171385,and 61901378+3 种基金in part by the Aeronautical Science Foundation of China under Grant 2020z073053004in part by the Foundation of the State Key Laboratory of Integrated Services Networks of Xidian University under Grant ISN21-06in part by the Key Research Program and Industrial Innovation Chain Project of Shaanxi Province under Grant 2019ZDLGY07-10in part by the Natural Science Fundamental Research Program of Shaanxi Province under Grant 2021JM-069.
文摘Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency.To tackle this problem,we propose an Unmanned Aerial Vehicle(UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its adjacent underloaded cell.To fully exploit its potential,we jointly optimize the UAV position,user association,spectrum allocation,and power allocation to maximize the sum-log-rate of all users in two adjacent cells.To tackle the complicated joint optimization problem,we first design a genetic-based algorithm to optimize the UAV position.Then,we simplify the problem by theoretical analysis and devise a low-complexity algorithm according to the branch-and-bound method,so as to obtain the optimal user association and spectrum allocation schemes.We further propose an iterative power allocation algorithm based on the sequential convex approximation theory.The simulation results indicate that the proposed UAV-assisted wireless network is superior to the terrestrial network in both utility and throughput,and the proposed algorithms can substantially improve the network performance in comparison with the other schemes.
文摘The human scalp harbors a diverse range of microbiome,much like other skin surfaces,where both beneficial and harmful microorganisms coexist.This study explores the possibility of balancing key scalp microorganisms,particularly Staphylococcus epidermidis,Staphylococcus aureus and Malassezia species.While Staphylococcus epidermidis plays a beneficial role in maintaining scalp health by producing antimicrobial proteins and supporting the skin barrier,Staphylococcus aureus is identified as a pathogen linked to skin infections and dandruff formation.Malassezia fungi degrade triglycerides in sebum into unsaturated fatty acids,exacerbating scalp conditions like dandruff.In order to promote the beneficial microbe while inhibit the harmful ones,we investigated the combination of 1.0 mM pyrrolidone carboxylate-zinc(PCA-Zn),0.2%malt oligosaccharides(MT:corn-derived oligosaccharide mainly containing maltotetraose)and 0.05 mM Hinokitiol on its microbial activity,which significantly enhanced the growth of Staphylococcus epidermidis while inhibiting both Staphylococcus aureus and Malassezia,offering insights into promising strategies for scalp care.
基金Supported by National Natural Scie nce Foun dation of China(Grant No.51875031)Youth Backb one Personal Project of Beijing(Grant No.2017000020124G018).
文摘Imbalance vibration is a typical failure mode of rotational machines and has significant negative effects on the efficiency,accuracy,and service life of equipment.To automatically reduce the imbalance vibration during the operational process,different types of active balancing actuators have been designed and widely applied in actual production.However,the existing electromagnetic-ring active balancing actuator is designed based on an axial excitation structure which can cause structural instability and has low electromagnetic driving efficiency.In this paper,a novel radial excitation structure and the working principle of an electromagnetic-ring active balancing actuator with a combined driving strategy are presented in detail.Then,based on a finite element model,the performance parameters of the actuator are analyzed,and reasonable design parameters are obtained.Self-locking torque measurements and comparative static and dynamic experiments are performed to validate the self-locking torque and driving efficiency of the actuator.The results indicate that this novel active balancing actuator has sufficient self-locking torque,achieves normal step rotation at 2000 r/min,and reduces the driving voltage by 12.5%.The proposed novel balancing actuator using radial excitation and a combination of permanent magnets and soft-iron blocks has improved electromagnetic efficiency and a more stable and compact structure.
