Drawing upon self-determination theory,this study examines the effects of vicarious abusive supervision on third-party’s self-efficacy and task performance within organizational contexts.Data were collected via surve...Drawing upon self-determination theory,this study examines the effects of vicarious abusive supervision on third-party’s self-efficacy and task performance within organizational contexts.Data were collected via surveys from 337 employees across diverse organizations.The results indicate that vicarious abusive supervision significantly undermines both self-efficacy and task performance among employees who are indirectly exposed to such behavior but not directly targeted.Furthermore,self-efficacy serves as a mediator between vicarious abusive supervision and task performance;however,this mediating effect is attenuated for employees with a high promotion focus.These findings provide valuable theoretical and practical insights,particularly in the domain of organizational behavior,by emphasizing the critical role of promotion focus in mitigating the negative effects of vicarious abusive supervision.This research contributes to the organizational behavior literature by shifting the focus from the traditional supervisor-subordinate dynamic to a third-party perspective,thereby enriching our understanding of how vicarious abusive supervision impacts employees within organizational settings.The study underscores the importance of self-efficacy and promotion focus as key factors in unethical leadership contexts.展开更多
In the context of intelligent manufacturing,the modern hot strip mill process(HSMP)shows characteristics such as diversification of products,multi-specification batch production,and demand-oriented customization.These...In the context of intelligent manufacturing,the modern hot strip mill process(HSMP)shows characteristics such as diversification of products,multi-specification batch production,and demand-oriented customization.These characteristics pose significant challenges to ensuring process stability and consistency of product performance.Therefore,exploring the potential relationship between product performance and the production process,and developing a comprehensive performance evaluation method adapted to modern HSMP have become an urgent issue.A comprehensive performance evaluation method for HSMP by integrating multi-task learning and stacked performance-related autoencoder is proposed to solve the problems such as incomplete performance indicators(PIs)data,insufficient real-time acquisition requirements,and coupling of multiple PIs.First,according to the existing Chinese standards,a comprehensive performance evaluation grade strategy for strip steel is designed.The random forest model is established to predict and complete the parts of PIs data that could not be obtained in real-time.Second,a stacked performance-related autoencoder(SPAE)model is proposed to extract the deep features closely related to the product performance.Then,considering the correlation between PIs,the multi-task learning framework is introduced to output the subitem ratings and comprehensive product performance rating results of the strip steel online in real-time,where each task represents a subitem of comprehensive performance.Finally,the effectiveness of the method is verified on a real HSMP dataset,and the results show that the accuracy of the proposed method is as high as 94.8%,which is superior to the other comparative methods.展开更多
The adsorptive denitrification performance of MIL-101(Cr)-0.5 toward pyridine,aniline or quinoline in simulated fuels with basic nitrogen content of 1732μg/g was evaluated separately.Furthermore,the effects of adsorp...The adsorptive denitrification performance of MIL-101(Cr)-0.5 toward pyridine,aniline or quinoline in simulated fuels with basic nitrogen content of 1732μg/g was evaluated separately.Furthermore,the effects of adsorption temperature,adsorption time and adsorbent dosage on their adsorptive denitrification performance were systematically investigated.The experimental results demonstrated that under a fixed adsorbent dosage of 0.05 g and a simulated fuel volume of 10 mL,the optimal removal efficiency for aniline was achieved at 30℃ within 30 min,whereas higher temperatures and longer times(40℃and 40 min)were required for effective removal of pyridine and quinoline.Density Functional Theory(DFT)calculations were conducted via Materials Studio(MS)software to study the adsorptive denitrification mechanism of MIL-101(Cr)toward these three basic nitrogen-containing compounds.The simulation calculation results revealed that the interaction between pyridine and MIL-101(Cr)primarily involved coordination adsorption.In contrast,the interaction between aniline or quinoline and MIL-101(Cr)proceeded mainly through coordination,with additional contributions fromπ-complexation and hydrogen bonding.The overall adsorption strength order is pyridine>aniline>quinoline.During the adsorption process,pyridine and quinoline transfer electrons to the MIL-101(Cr)surface through the H→C→N→Cr^(3+)pathway,while aniline transfers electrons to the MIL-101(Cr)surface through various pathways,including N→Cr^(3+),N→C→Cr^(3+)and N→H→O.Furthermore,adsorption kinetics studies indicated that the adsorption processes for all three basic nitrogen-containing compounds followed the quasi second order kinetic models.The experimental results on the effect of benzene on the adsorptive denitrification performance of MIL-101(Cr)-0.5 demonstrated that benzene exerted a more significant impact on the adsorption of aniline and quinoline.Finally,the adsorbent was regenerated using ethanol washing.It was found that MIL-101(Cr)-0.5 retained stable denitrification performance after two regeneration cycles.展开更多
To elucidate the effect of calcite-regulated activated carbon(AC)structure on low-temperature denitrification performance of SCR catalysts,this work prepared a series of Mn-Ce/De-AC-xCaCO_(3)(x is the calcite content ...To elucidate the effect of calcite-regulated activated carbon(AC)structure on low-temperature denitrification performance of SCR catalysts,this work prepared a series of Mn-Ce/De-AC-xCaCO_(3)(x is the calcite content in coal)catalysts were prepared by the incipient wetness impregnation method,followed by acid washing to remove calcium-containing minerals.Comprehensive characterization and low-temperature denitrification tests revealed that calcite-induced structural modulation of coal-derived AC significantly enhances catalytic activity.Specifically,NO conversion increased from 88.3%of Mn-Ce/De-AC to 91.7%of Mn-Ce/De-AC-1CaCO_(3)(210℃).The improved SCR denitrification activity results from the enhancement of physicochemical properties including higher Mn^(4+)content and Ce^(4+)/Ce^(3+)ratio,an abundance of chemisorbed oxygen and acidic sites,which could strengthen the SCR reaction pathways(richer NH_(3)activated species and bidentate nitrate active species).Therefore,NO removal is enhanced.展开更多
Task scheduling in cloud computing is a multi-objective optimization problem,often involving conflicting objectives such as minimizing execution time,reducing operational cost,and maximizing resource utilization.Howev...Task scheduling in cloud computing is a multi-objective optimization problem,often involving conflicting objectives such as minimizing execution time,reducing operational cost,and maximizing resource utilization.However,traditional approaches frequently rely on single-objective optimization methods which are insufficient for capturing the complexity of such problems.To address this limitation,we introduce MDMOSA(Multi-objective Dwarf Mongoose Optimization with Simulated Annealing),a hybrid that integrates multi-objective optimization for efficient task scheduling in Infrastructure-as-a-Service(IaaS)cloud environments.MDMOSA harmonizes the exploration capabilities of the biologically inspired Dwarf Mongoose Optimization(DMO)with the exploitation strengths of Simulated Annealing(SA),achieving a balanced search process.The algorithm aims to optimize task allocation by reducing makespan and financial cost while improving system resource utilization.We evaluate MDMOSA through extensive simulations using the real-world Google Cloud Jobs(GoCJ)dataset within the CloudSim environment.Comparative analysis against benchmarked algorithms such as SMOACO,MOTSGWO,and MFPAGWO reveals that MDMOSA consistently achieves superior performance in terms of scheduling efficiency,cost-effectiveness,and scalability.These results confirm the potential of MDMOSA as a robust and adaptable solution for resource scheduling in dynamic and heterogeneous cloud computing infrastructures.展开更多
Purpose:ATLAS is a cross-sectional study aiming to investigate environmental and genetic determinants of athletic performance in healthy Greek competitive athletes(CA).This article presents the study design,investigat...Purpose:ATLAS is a cross-sectional study aiming to investigate environmental and genetic determinants of athletic performance in healthy Greek competitive athletes(CA).This article presents the study design,investigates the muscle strength performance(MSP)of 289 adult and teenage CA,exercisers,and physically inactive individuals(PI),and proposes predictive models of MSP for adults.Methods:Muscle maximal,speed,and explosive strength(MMS/MSS/MES)at unilateral maximal concentric flexion and extension contraction(FC/EC)were evaluated using Biodex System 3 PRO^(TM)at 60°/s,180°/s,and 300°/s,while additional performance markers were assessed through field ergometric testing.Participants were interviewed about their lifestyle,dietary habits,physical activity,injury,and medical history.Body composition was assessed via bioelectrical impedance.gDNA was extracted from biochemical samples and then genotyped.Statistical analysis was conducted using IBM SPSS Statistics v21.0 and R.Results:Age,fitness,and sex impacted correlations of MSP with body composition and anthropometric measurements(p<0.05).Among CA,females outperformed males in accuracy(p<0.001)while,males outperformed females in anaerobic power,MSP,speed,and endurance(p<0.001).Adult CA outperformed exercisers and PI in MMS,MSS,and MES(p<0.05).Multiple linear regression models,with predictors age,FFM,body extremity,training load explained the majority of variation in MMS(R^(2)_(adj):71.4%–88.9%),MSS(R^(2)_(adj):64.8%–78.4%),and MES(R^(2)_(adj):52.7%–68.4%)at EC,FC,and their mean(p<0.001).Conclusions:Muscle-strengthening strategies should be customized according to individual fitness levels,body composition,and anthropometric measurements.The innovative sex-specific regression models assessing MMS,MSS,and MES at EC and FC provide a framework for personalizing rehabilitation and skill-specific training strategies.展开更多
In scenarios where ground-based cloud computing infrastructure is unavailable,unmanned aerial vehicles(UAVs)act as mobile edge computing(MEC)servers to provide on-demand computation services for ground terminals.To ad...In scenarios where ground-based cloud computing infrastructure is unavailable,unmanned aerial vehicles(UAVs)act as mobile edge computing(MEC)servers to provide on-demand computation services for ground terminals.To address the challenge of jointly optimizing task scheduling and UAV trajectory under limited resources and high mobility of UAVs,this paper presents PER-MATD3,a multi-agent deep reinforcement learning algorithm with prioritized experience replay(PER)into the Centralized Training with Decentralized Execution(CTDE)framework.Specifically,PER-MATD3 enables each agent to learn a decentralized policy using only local observations during execution,while leveraging a shared replay buffer with prioritized sampling and centralized critic during training to accelerate convergence and improve sample efficiency.Simulation results show that PER-MATD3 reduces average task latency by up to 23%,improves energy efficiency by 21%,and enhances service coverage compared to state-of-the-art baselines,demonstrating its effectiveness and practicality in scenarios without terrestrial networks.展开更多
The cloud-fog computing paradigm has emerged as a novel hybrid computing model that integrates computational resources at both fog nodes and cloud servers to address the challenges posed by dynamic and heterogeneous c...The cloud-fog computing paradigm has emerged as a novel hybrid computing model that integrates computational resources at both fog nodes and cloud servers to address the challenges posed by dynamic and heterogeneous computing networks.Finding an optimal computational resource for task offloading and then executing efficiently is a critical issue to achieve a trade-off between energy consumption and transmission delay.In this network,the task processed at fog nodes reduces transmission delay.Still,it increases energy consumption,while routing tasks to the cloud server saves energy at the cost of higher communication delay.Moreover,the order in which offloaded tasks are executed affects the system’s efficiency.For instance,executing lower-priority tasks before higher-priority jobs can disturb the reliability and stability of the system.Therefore,an efficient strategy of optimal computation offloading and task scheduling is required for operational efficacy.In this paper,we introduced a multi-objective and enhanced version of Cheeta Optimizer(CO),namely(MoECO),to jointly optimize the computation offloading and task scheduling in cloud-fog networks to minimize two competing objectives,i.e.,energy consumption and communication delay.MoECO first assigns tasks to the optimal computational nodes and then the allocated tasks are scheduled for processing based on the task priority.The mathematical modelling of CO needs improvement in computation time and convergence speed.Therefore,MoECO is proposed to increase the search capability of agents by controlling the search strategy based on a leader’s location.The adaptive step length operator is adjusted to diversify the solution and thus improves the exploration phase,i.e.,global search strategy.Consequently,this prevents the algorithm from getting trapped in the local optimal solution.Moreover,the interaction factor during the exploitation phase is also adjusted based on the location of the prey instead of the adjacent Cheetah.This increases the exploitation capability of agents,i.e.,local search capability.Furthermore,MoECO employs a multi-objective Pareto-optimal front to simultaneously minimize designated objectives.Comprehensive simulations in MATLAB demonstrate that the proposed algorithm obtains multiple solutions via a Pareto-optimal front and achieves an efficient trade-off between optimization objectives compared to baseline methods.展开更多
In composite solid propellants with high aluminum(Al)content and low burning rate,incomplete combustion of the Al powder may occur.In this study,varying lithium(Li)content in Al-Li alloy powder was utilized instead of...In composite solid propellants with high aluminum(Al)content and low burning rate,incomplete combustion of the Al powder may occur.In this study,varying lithium(Li)content in Al-Li alloy powder was utilized instead of pure aluminum particles to mitigate agglomeration and enhance the combustion efficiency of solid propellants(Combustion efficiency herein refers to the completeness of metallic fuel oxidation,quantified as the ratio of actual-to-theoretical energy released during combustion)with high Al content and low burning rates.The impact of Al-Li alloy with different Li contents on combustion and agglomeration of solid propellant was investigated using explosion heat,combustion heat,differential thermal analysis(DTA),thermos-gravimetric analysis(TG),dynamic high-pressure combustion test,ignition experiment of small solid rocket motor(SRM)tests,condensation combustion product collection,and X-ray diffraction techniques(XRD).Compared with pure Al,Al-Li alloys exhibit higher combustion heat,which contributes to improved combustion efficiency in Al-Li alloy-containing propellants.DTA and TG analyses demonstrated higher reactivity and lower ignition temperatures for Al-Li alloys.High-pressure combustion experiments at 5 MPa showed that Al-Li alloy fuel significantly decreases combustion agglomeration.The results from theφ75 mm andφ165 mm SRM and XRD tests further support this finding.This study provides novel insights into the combustion and agglomeration behaviors of high-Al,low-burning-rate composite solid propellants and supports the potential application of Al-Li alloys in advanced propellant formulations.展开更多
The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-lear...The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.展开更多
In the context of the revolution in new technologies,a key question is whether the rapid growth of the digital economy,driven by digital technologies,has improved regional innovation performance.Using inter-provincial...In the context of the revolution in new technologies,a key question is whether the rapid growth of the digital economy,driven by digital technologies,has improved regional innovation performance.Using inter-provincial panel data from China(2012–2022)and adopting a business environment perspective,this study applies a Panel Extended Regression Model(PERM),a Panel Simultaneous Equation Model(PSEM),and a Tobit-IV model to analyze how the development of the digital economy influences regional innovation.The results reveal a pronounced U-shaped relationship between the digital economy and the regional innovation performance at the provincial level in China,with the business environment serving as a significant mediator in this relationship.Moreover,regional innovation performance in China exhibits a“ratchet effect,”with the impact of the digital economy varying markedly across regions.While the eastern and western regions have entered an upward phase,whereby the digital economy boosts innovation,the central region displays a weaker effect.Further analysis indicates that the synergy between the business environment and the digital economy in driving innovation remains suboptimal.These findings were supported by robust checks.This study offers theoretical insights and empirical evidence that support the coordinated development of digital government and the digital factor market,as well as business environment reforms that are in alignment with the innovation demands of the digital era.展开更多
This work examines the microstructure and corrosion properties of fine-grained Al 7075 across different regions under varying cooling conditions during friction stir welding.The findings demonstrate that forced coolin...This work examines the microstructure and corrosion properties of fine-grained Al 7075 across different regions under varying cooling conditions during friction stir welding.The findings demonstrate that forced cooling significantly improves the corrosion resistance of the welded joints.Specifically,the corrosion resistance was the highest in the stir zone,followed by the thermo-mechanical affected zone,and then the heat affected zone.Forced cooling mitigates grain growth by controlling the welding thermal effects,thereby increasing the proportion ofΣ3 grain boundaries.The modification of these microstructural characteristics promotes the formation of a dense oxide layer,thereby enhancing the corrosion resistance.Furthermore,forced cooling mitigates the precipitation and coarsening of the anodic phase in the stir zone,which in turn reduces the susceptibility of the joint to pitting corrosion.Additionally,the lower recrystallization texture content in the joint,resulting from forced cooling,contributes to a reduction in the number of corrosion-active sites,thereby further improving the corrosion performance of the welded joint.展开更多
Al/NH_(4)CoF_(3)-Φ(Φ=0.5,1.0,1.5,2.0,and 3.0)binary composites and Al-NH_(4)CoF_(3)@P(VDF-HFP)ternary composites are fabricated via ultrasonication-assisted blending and electrostatic spraying.The effect of equivale...Al/NH_(4)CoF_(3)-Φ(Φ=0.5,1.0,1.5,2.0,and 3.0)binary composites and Al-NH_(4)CoF_(3)@P(VDF-HFP)ternary composites are fabricated via ultrasonication-assisted blending and electrostatic spraying.The effect of equivalence ratio(Φ)on the reaction properties is systematically investigated in the binary Al/NH_(4)CoF_(3)system.For ternary systems,electrostatic spraying allows both components to be efficiently encapsulated by P(VDF-HFP)and to achieve structural stabilization and enhanced reactivity through synergistic interfacial interactions.Morphological analysis using SEM/TEM revealed that P(VDF-HFP)formed a protective layer on Al and NH_(4)CoF_(3)particles,improving dispersion,hydrophobicity(water contact angle increased by 80.5%compared to physically mixed composites),and corrosion resistance.Thermal decomposition of NH_(4)CoF_(3)occurred at 265℃,releasing NH_(3)and HF,which triggered exothermic reactions with Al.The ternary composites exhibited a narrowed main reaction temperature range and concentrated heat release,attributed to improved interfacial contact and polymer decomposition.Combustion tests demonstrated that Al-NH_(4)CoF_(3)@P(VDF-HFP)achieved self-sustaining combustion.In addition,a simple validation was done by replacing the Al component in the aluminium-containing propellant,demonstrating its potential application in the propellant field.This work establishes a novel strategy for designing stable,high-energy composites with potential applications in advanced propulsion systems.展开更多
Isolation technology can reduce the type of structural damage that earthquakes cause.A new type of composite sliding-rolling friction composite seismic isolation bearing(SRF)with composite sliding friction and rolling...Isolation technology can reduce the type of structural damage that earthquakes cause.A new type of composite sliding-rolling friction composite seismic isolation bearing(SRF)with composite sliding friction and rolling friction is proposed.SRF is capable of realizing a parallel arrangement of sliding friction and rolling friction,and the coefficient of dynamic friction shows variability.The proposed static tests on composite bearings were conducted to investigate the effects of the number of shims,loading speed and vertical pressure on the dynamic friction factor.Test results show that the coefficient of dynamic friction first generally decreases and then increases with an increase in sliding speed,prior to again decreasing with an increase in vertical pressure.The dynamic friction factor increases and then decreases with an increase in the number of shims for a four-roll ball.It decreases and then increases with an increase in the number of shims for a five-roll ball.Based on finite element analysis,modeling and analyzing the effects of the coefficient of friction,the number of balls and the number of shims on the hysteresis performance of the support and derive its skeleton curve.The SRF hysteretic performance,dynamic friction factor and the number of rolling balls and shims show significant correlation.展开更多
Background The decline in reproductive performance of aged hens is mainly attributed to oxidative damage in reproductive organs,hepatic lipid metabolism disorders,and intestinal microbiota dysbiosis.Glycyrrhizin(GL)ha...Background The decline in reproductive performance of aged hens is mainly attributed to oxidative damage in reproductive organs,hepatic lipid metabolism disorders,and intestinal microbiota dysbiosis.Glycyrrhizin(GL)has been proven to enhance antioxidant capacity,regulate lipid metabolism and gut microbiota in mammals,but its efficacy in hens remains unclear.Hence,this study aimed to investigate whether dietary GL supplementation improves reproductive performance in hens during the late laying stage by modulating intestinal microbiota composition,hepatic lipid metabolism and ovarian antioxidant status.Results Dietary supplementation with 100 mg/kg GL significantly improved the egg production rate,egg quality,and hatching rate in aged breeder hens(P<0.05).GL supplementation also increased the serum levels of HDLC,TP and ALB,and enhanced the antioxidant capacity in both serum and ovary(P<0.05).In addition,dietary GL elevated the serum progesterone(P4)levels by enhancing the transcription level of steroid synthesis key enzymes(CYP11A1 and 3β-HSD)in the ovary(P<0.05).Dietary GL also promoted the synthesis and transport of vitellogenin(VTG)by upregulating the VTG-Ⅱ(P<0.05)and APOV1(P=0.077)expression levels in the liver,thereby increasing the number of grade follicles and small yellow follicles.Moreover,dietary GL enhanced hepatic fatty acidβ-oxidation by upregulating PPARαand CPT-I(P<0.05),and downregulating ACC expression levels(P<0.05).In agreement,liver metabolomics analysis revealed that dietary GL supplementation significantly altered hepatic metabolism,with 389 differentially identified metabolites(P<0.05).The key metabolites(e.g.,taurocholic acid,tauroursodeoxycholic acid,nicotinuric acid,glycodeoxycholic acid(hydrate))were identified,and they were mainly functionally enriched in betaalanine metabolism nicotinate,taurine and hypotaurine metabolism(P<0.05).Finally,16S rRNA gene sequencing revealed that dietary GL reversed age-induced changes in gut microbiota composition,characterized by a significant increase in Lactobacillus abundance and a decrease in Bacteroides(P<0.05).Conclusions These results collectively demonstrate that dietary supplementation with 100 mg/kg GL improved reproductive performance by reversing age-induced changes in gut microbiota,enhancing hepatic vitellogenin synthesis,and ameliorating ovarian function in aged breeder hens.This study suggests that dietary GL is a potential strategy to improve reproductive performance in broiler breeder hens during the late laying period.展开更多
The core components of an aircraft and the source of its lift are its wings,but lift generation is disrupted by the high temperature and pressure generated on the wing surface when an aircraft gun is fired.Here,to inv...The core components of an aircraft and the source of its lift are its wings,but lift generation is disrupted by the high temperature and pressure generated on the wing surface when an aircraft gun is fired.Here,to investigate how this process influences the aerodynamic parameters of aircraft wings,the k-ωshearstress-transport turbulence model and the nested dynamic grid technique are used to analyze numerically the transient process of the muzzle jet of a 30-mm small-caliber aircraft gun in highaltitude(10 km)flight with an incoming Mach number of Ma=0.8.For comparison,two other models are established,one with no projectile and the other with no wing.The results indicate that when the aircraft gun is fired,the muzzle jet acts on the wing,creating a pressure field thereon.The uneven distribution of high pressure greatly reduces the lift of the aircraft,causing oscillations in its drag and disrupting its dynamic balance,thereby affecting its flight speed and attitude.Meanwhile,the muzzle jet is obstructed by the wing,and its flow field is distorted and deformed,developing upward toward the wing.Because of the influence of the incoming flow,the shockwave front of the projectile changes from a smooth spherical shape to an irregular one,and the motion parameters of the projectile are also greatly affected by oscillations.The present results provide an important theoretical basis for how the guns of fighter aircraft influence the aerodynamic performance of the wings.展开更多
To address the issues of insufficient and imbalanced data samples in proton exchange membrane fuel cell(PEMFC)performance degradation prediction,this study proposes a data augmentation-based model to predict PEMFC per...To address the issues of insufficient and imbalanced data samples in proton exchange membrane fuel cell(PEMFC)performance degradation prediction,this study proposes a data augmentation-based model to predict PEMFC performance degradation.Firstly,an improved generative adversarial network(IGAN)with adaptive gradient penalty coefficient is proposed to address the problems of excessively fast gradient descent and insufficient diversity of generated samples.Then,the IGANis used to generate datawith a distribution analogous to real data,therebymitigating the insufficiency and imbalance of original PEMFC samples and providing the predictionmodel with training data rich in feature information.Finally,a convolutional neural network-bidirectional long short-termmemory(CNN-BiLSTM)model is adopted to predict PEMFC performance degradation.Experimental results show that the data generated by the proposed IGAN exhibits higher quality than that generated by the original GAN,and can fully characterize and enrich the original data’s features.Using the augmented data,the prediction accuracy of the CNN-BiLSTM model is significantly improved,rendering it applicable to tasks of predicting PEMFC performance degradation.展开更多
In recent years,fog computing has become an important environment for dealing with the Internet of Things.Fog computing was developed to handle large-scale big data by scheduling tasks via cloud computing.Task schedul...In recent years,fog computing has become an important environment for dealing with the Internet of Things.Fog computing was developed to handle large-scale big data by scheduling tasks via cloud computing.Task scheduling is crucial for efficiently handling IoT user requests,thereby improving system performance,cost,and energy consumption across nodes in cloud computing.With the large amount of data and user requests,achieving the optimal solution to the task scheduling problem is challenging,particularly in terms of cost and energy efficiency.In this paper,we develop novel strategies to save energy consumption across nodes in fog computing when users execute tasks through the least-cost paths.Task scheduling is developed using modified artificial ecosystem optimization(AEO),combined with negative swarm operators,Salp Swarm Algorithm(SSA),in order to competitively optimize their capabilities during the exploitation phase of the optimal search process.In addition,the proposed strategy,Enhancement Artificial Ecosystem Optimization Salp Swarm Algorithm(EAEOSSA),attempts to find the most suitable solution.The optimization that combines cost and energy for multi-objective task scheduling optimization problems.The backpack problem is also added to improve both cost and energy in the iFogSim implementation as well.A comparison was made between the proposed strategy and other strategies in terms of time,cost,energy,and productivity.Experimental results showed that the proposed strategy improved energy consumption,cost,and time over other algorithms.Simulation results demonstrate that the proposed algorithm increases the average cost,average energy consumption,and mean service time in most scenarios,with average reductions of up to 21.15%in cost and 25.8%in energy consumption.展开更多
Under earthquake action, different site conditions have a notable impact on the dynamic response of high-speed railway bridges after earthquakes, which in turn poses a threat to the running stability of trains in the ...Under earthquake action, different site conditions have a notable impact on the dynamic response of high-speed railway bridges after earthquakes, which in turn poses a threat to the running stability of trains in the post-earthquake period. Therefore, establishing a calculation method for the post-earthquake train speed threshold that considers the influence of different site characteristics is of great engineering significance. Taking the CRTS Ⅲ slab track as the research object, this study is based on the track irregularity root mean square rate(TRR), which the authors proposed earlier to quantify the track regularity level. Using the nonlinear least squares fitting method, the mapping relationship between the TRR and the postearthquake train running performance indicators on bridges is established. Furthermore, the influence of laws governing site categories and train speeds on post-earthquake train running performance on bridges is analyzed, and a train speed threshold for bridges based on running performance under random site conditions is proposed. The research results indicate that all train running performance indicators increase significantly with the increase of train operating speed;different site categories have a significant impact on post-earthquake track residual deformation and train running stability. The greater the amplitude of postearthquake track alignment residual deformation, the lower the threshold for the stable running speed of trains after the earthquake, with the speed threshold decreasing by up to 20%. The research outcomes can provide technical references for the post-earthquake safe operation and maintenance of high-speed railway bridges under complex site conditions, as well as the formulation of targeted train speed control schemes.展开更多
文摘Drawing upon self-determination theory,this study examines the effects of vicarious abusive supervision on third-party’s self-efficacy and task performance within organizational contexts.Data were collected via surveys from 337 employees across diverse organizations.The results indicate that vicarious abusive supervision significantly undermines both self-efficacy and task performance among employees who are indirectly exposed to such behavior but not directly targeted.Furthermore,self-efficacy serves as a mediator between vicarious abusive supervision and task performance;however,this mediating effect is attenuated for employees with a high promotion focus.These findings provide valuable theoretical and practical insights,particularly in the domain of organizational behavior,by emphasizing the critical role of promotion focus in mitigating the negative effects of vicarious abusive supervision.This research contributes to the organizational behavior literature by shifting the focus from the traditional supervisor-subordinate dynamic to a third-party perspective,thereby enriching our understanding of how vicarious abusive supervision impacts employees within organizational settings.The study underscores the importance of self-efficacy and promotion focus as key factors in unethical leadership contexts.
基金supported by the National Natural Science Foundation of China(NSFC)under Grants(Nos.U21A20483,62373040 and 62273031).
文摘In the context of intelligent manufacturing,the modern hot strip mill process(HSMP)shows characteristics such as diversification of products,multi-specification batch production,and demand-oriented customization.These characteristics pose significant challenges to ensuring process stability and consistency of product performance.Therefore,exploring the potential relationship between product performance and the production process,and developing a comprehensive performance evaluation method adapted to modern HSMP have become an urgent issue.A comprehensive performance evaluation method for HSMP by integrating multi-task learning and stacked performance-related autoencoder is proposed to solve the problems such as incomplete performance indicators(PIs)data,insufficient real-time acquisition requirements,and coupling of multiple PIs.First,according to the existing Chinese standards,a comprehensive performance evaluation grade strategy for strip steel is designed.The random forest model is established to predict and complete the parts of PIs data that could not be obtained in real-time.Second,a stacked performance-related autoencoder(SPAE)model is proposed to extract the deep features closely related to the product performance.Then,considering the correlation between PIs,the multi-task learning framework is introduced to output the subitem ratings and comprehensive product performance rating results of the strip steel online in real-time,where each task represents a subitem of comprehensive performance.Finally,the effectiveness of the method is verified on a real HSMP dataset,and the results show that the accuracy of the proposed method is as high as 94.8%,which is superior to the other comparative methods.
基金Supported by Basic Scientific Research Project of the Liaoning Provincial Department of Education Has Been Unveiled to Facilitate Local Project Funding (JYTMS20230835)Enhanced Scientific Research Project Funded by the Departmentof Higher Education in Liaoning Province (General program)(JYTMS20230852)。
文摘The adsorptive denitrification performance of MIL-101(Cr)-0.5 toward pyridine,aniline or quinoline in simulated fuels with basic nitrogen content of 1732μg/g was evaluated separately.Furthermore,the effects of adsorption temperature,adsorption time and adsorbent dosage on their adsorptive denitrification performance were systematically investigated.The experimental results demonstrated that under a fixed adsorbent dosage of 0.05 g and a simulated fuel volume of 10 mL,the optimal removal efficiency for aniline was achieved at 30℃ within 30 min,whereas higher temperatures and longer times(40℃and 40 min)were required for effective removal of pyridine and quinoline.Density Functional Theory(DFT)calculations were conducted via Materials Studio(MS)software to study the adsorptive denitrification mechanism of MIL-101(Cr)toward these three basic nitrogen-containing compounds.The simulation calculation results revealed that the interaction between pyridine and MIL-101(Cr)primarily involved coordination adsorption.In contrast,the interaction between aniline or quinoline and MIL-101(Cr)proceeded mainly through coordination,with additional contributions fromπ-complexation and hydrogen bonding.The overall adsorption strength order is pyridine>aniline>quinoline.During the adsorption process,pyridine and quinoline transfer electrons to the MIL-101(Cr)surface through the H→C→N→Cr^(3+)pathway,while aniline transfers electrons to the MIL-101(Cr)surface through various pathways,including N→Cr^(3+),N→C→Cr^(3+)and N→H→O.Furthermore,adsorption kinetics studies indicated that the adsorption processes for all three basic nitrogen-containing compounds followed the quasi second order kinetic models.The experimental results on the effect of benzene on the adsorptive denitrification performance of MIL-101(Cr)-0.5 demonstrated that benzene exerted a more significant impact on the adsorption of aniline and quinoline.Finally,the adsorbent was regenerated using ethanol washing.It was found that MIL-101(Cr)-0.5 retained stable denitrification performance after two regeneration cycles.
基金Supported by the Science and Technology Cooperation and Exchange special project of Cooperation of Shanxi Province(202404041101014)the Fundamental Research Program of Shanxi Province(202403021212333)+3 种基金the Joint Funds of the National Natural Science Foundation of China(U24A20555)the Lvliang Key R&D of University-Local Cooperation(2023XDHZ10)the Initiation Fund for Doctoral Research of Taiyuan University of Science and Technology(20242026)the Outstanding Doctor Funding Award of Shanxi Province(20242080).
文摘To elucidate the effect of calcite-regulated activated carbon(AC)structure on low-temperature denitrification performance of SCR catalysts,this work prepared a series of Mn-Ce/De-AC-xCaCO_(3)(x is the calcite content in coal)catalysts were prepared by the incipient wetness impregnation method,followed by acid washing to remove calcium-containing minerals.Comprehensive characterization and low-temperature denitrification tests revealed that calcite-induced structural modulation of coal-derived AC significantly enhances catalytic activity.Specifically,NO conversion increased from 88.3%of Mn-Ce/De-AC to 91.7%of Mn-Ce/De-AC-1CaCO_(3)(210℃).The improved SCR denitrification activity results from the enhancement of physicochemical properties including higher Mn^(4+)content and Ce^(4+)/Ce^(3+)ratio,an abundance of chemisorbed oxygen and acidic sites,which could strengthen the SCR reaction pathways(richer NH_(3)activated species and bidentate nitrate active species).Therefore,NO removal is enhanced.
文摘Task scheduling in cloud computing is a multi-objective optimization problem,often involving conflicting objectives such as minimizing execution time,reducing operational cost,and maximizing resource utilization.However,traditional approaches frequently rely on single-objective optimization methods which are insufficient for capturing the complexity of such problems.To address this limitation,we introduce MDMOSA(Multi-objective Dwarf Mongoose Optimization with Simulated Annealing),a hybrid that integrates multi-objective optimization for efficient task scheduling in Infrastructure-as-a-Service(IaaS)cloud environments.MDMOSA harmonizes the exploration capabilities of the biologically inspired Dwarf Mongoose Optimization(DMO)with the exploitation strengths of Simulated Annealing(SA),achieving a balanced search process.The algorithm aims to optimize task allocation by reducing makespan and financial cost while improving system resource utilization.We evaluate MDMOSA through extensive simulations using the real-world Google Cloud Jobs(GoCJ)dataset within the CloudSim environment.Comparative analysis against benchmarked algorithms such as SMOACO,MOTSGWO,and MFPAGWO reveals that MDMOSA consistently achieves superior performance in terms of scheduling efficiency,cost-effectiveness,and scalability.These results confirm the potential of MDMOSA as a robust and adaptable solution for resource scheduling in dynamic and heterogeneous cloud computing infrastructures.
文摘Purpose:ATLAS is a cross-sectional study aiming to investigate environmental and genetic determinants of athletic performance in healthy Greek competitive athletes(CA).This article presents the study design,investigates the muscle strength performance(MSP)of 289 adult and teenage CA,exercisers,and physically inactive individuals(PI),and proposes predictive models of MSP for adults.Methods:Muscle maximal,speed,and explosive strength(MMS/MSS/MES)at unilateral maximal concentric flexion and extension contraction(FC/EC)were evaluated using Biodex System 3 PRO^(TM)at 60°/s,180°/s,and 300°/s,while additional performance markers were assessed through field ergometric testing.Participants were interviewed about their lifestyle,dietary habits,physical activity,injury,and medical history.Body composition was assessed via bioelectrical impedance.gDNA was extracted from biochemical samples and then genotyped.Statistical analysis was conducted using IBM SPSS Statistics v21.0 and R.Results:Age,fitness,and sex impacted correlations of MSP with body composition and anthropometric measurements(p<0.05).Among CA,females outperformed males in accuracy(p<0.001)while,males outperformed females in anaerobic power,MSP,speed,and endurance(p<0.001).Adult CA outperformed exercisers and PI in MMS,MSS,and MES(p<0.05).Multiple linear regression models,with predictors age,FFM,body extremity,training load explained the majority of variation in MMS(R^(2)_(adj):71.4%–88.9%),MSS(R^(2)_(adj):64.8%–78.4%),and MES(R^(2)_(adj):52.7%–68.4%)at EC,FC,and their mean(p<0.001).Conclusions:Muscle-strengthening strategies should be customized according to individual fitness levels,body composition,and anthropometric measurements.The innovative sex-specific regression models assessing MMS,MSS,and MES at EC and FC provide a framework for personalizing rehabilitation and skill-specific training strategies.
基金supported by the National Natural Science Foundation of China under Grant No.61701100.
文摘In scenarios where ground-based cloud computing infrastructure is unavailable,unmanned aerial vehicles(UAVs)act as mobile edge computing(MEC)servers to provide on-demand computation services for ground terminals.To address the challenge of jointly optimizing task scheduling and UAV trajectory under limited resources and high mobility of UAVs,this paper presents PER-MATD3,a multi-agent deep reinforcement learning algorithm with prioritized experience replay(PER)into the Centralized Training with Decentralized Execution(CTDE)framework.Specifically,PER-MATD3 enables each agent to learn a decentralized policy using only local observations during execution,while leveraging a shared replay buffer with prioritized sampling and centralized critic during training to accelerate convergence and improve sample efficiency.Simulation results show that PER-MATD3 reduces average task latency by up to 23%,improves energy efficiency by 21%,and enhances service coverage compared to state-of-the-art baselines,demonstrating its effectiveness and practicality in scenarios without terrestrial networks.
基金appreciation to the Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R384)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The cloud-fog computing paradigm has emerged as a novel hybrid computing model that integrates computational resources at both fog nodes and cloud servers to address the challenges posed by dynamic and heterogeneous computing networks.Finding an optimal computational resource for task offloading and then executing efficiently is a critical issue to achieve a trade-off between energy consumption and transmission delay.In this network,the task processed at fog nodes reduces transmission delay.Still,it increases energy consumption,while routing tasks to the cloud server saves energy at the cost of higher communication delay.Moreover,the order in which offloaded tasks are executed affects the system’s efficiency.For instance,executing lower-priority tasks before higher-priority jobs can disturb the reliability and stability of the system.Therefore,an efficient strategy of optimal computation offloading and task scheduling is required for operational efficacy.In this paper,we introduced a multi-objective and enhanced version of Cheeta Optimizer(CO),namely(MoECO),to jointly optimize the computation offloading and task scheduling in cloud-fog networks to minimize two competing objectives,i.e.,energy consumption and communication delay.MoECO first assigns tasks to the optimal computational nodes and then the allocated tasks are scheduled for processing based on the task priority.The mathematical modelling of CO needs improvement in computation time and convergence speed.Therefore,MoECO is proposed to increase the search capability of agents by controlling the search strategy based on a leader’s location.The adaptive step length operator is adjusted to diversify the solution and thus improves the exploration phase,i.e.,global search strategy.Consequently,this prevents the algorithm from getting trapped in the local optimal solution.Moreover,the interaction factor during the exploitation phase is also adjusted based on the location of the prey instead of the adjacent Cheetah.This increases the exploitation capability of agents,i.e.,local search capability.Furthermore,MoECO employs a multi-objective Pareto-optimal front to simultaneously minimize designated objectives.Comprehensive simulations in MATLAB demonstrate that the proposed algorithm obtains multiple solutions via a Pareto-optimal front and achieves an efficient trade-off between optimization objectives compared to baseline methods.
基金the National Natural Science Foundation of China(Grant No.U2441263)for financial support of this work。
文摘In composite solid propellants with high aluminum(Al)content and low burning rate,incomplete combustion of the Al powder may occur.In this study,varying lithium(Li)content in Al-Li alloy powder was utilized instead of pure aluminum particles to mitigate agglomeration and enhance the combustion efficiency of solid propellants(Combustion efficiency herein refers to the completeness of metallic fuel oxidation,quantified as the ratio of actual-to-theoretical energy released during combustion)with high Al content and low burning rates.The impact of Al-Li alloy with different Li contents on combustion and agglomeration of solid propellant was investigated using explosion heat,combustion heat,differential thermal analysis(DTA),thermos-gravimetric analysis(TG),dynamic high-pressure combustion test,ignition experiment of small solid rocket motor(SRM)tests,condensation combustion product collection,and X-ray diffraction techniques(XRD).Compared with pure Al,Al-Li alloys exhibit higher combustion heat,which contributes to improved combustion efficiency in Al-Li alloy-containing propellants.DTA and TG analyses demonstrated higher reactivity and lower ignition temperatures for Al-Li alloys.High-pressure combustion experiments at 5 MPa showed that Al-Li alloy fuel significantly decreases combustion agglomeration.The results from theφ75 mm andφ165 mm SRM and XRD tests further support this finding.This study provides novel insights into the combustion and agglomeration behaviors of high-Al,low-burning-rate composite solid propellants and supports the potential application of Al-Li alloys in advanced propellant formulations.
基金financially supported by the National Science Fund for Distinguished Young Scholars,China(No.52025041)the National Natural Science Foundation of China(Nos.52450003,U2341267,and 52174294)+1 种基金the National Postdoctoral Program for Innovative Talents,China(No.BX20240437)the Fundamental Research Funds for the Central Universities,China(Nos.FRF-IDRY-23-037 and FRF-TP-20-02C2)。
文摘The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.
基金National Social Science Fund of China(18KXS009)the Sichuan Provincial Soft Science Program(22JDR0261)the Sichuan University“From 0 to 1”Innovation Research Program(2021CXC10)。
文摘In the context of the revolution in new technologies,a key question is whether the rapid growth of the digital economy,driven by digital technologies,has improved regional innovation performance.Using inter-provincial panel data from China(2012–2022)and adopting a business environment perspective,this study applies a Panel Extended Regression Model(PERM),a Panel Simultaneous Equation Model(PSEM),and a Tobit-IV model to analyze how the development of the digital economy influences regional innovation.The results reveal a pronounced U-shaped relationship between the digital economy and the regional innovation performance at the provincial level in China,with the business environment serving as a significant mediator in this relationship.Moreover,regional innovation performance in China exhibits a“ratchet effect,”with the impact of the digital economy varying markedly across regions.While the eastern and western regions have entered an upward phase,whereby the digital economy boosts innovation,the central region displays a weaker effect.Further analysis indicates that the synergy between the business environment and the digital economy in driving innovation remains suboptimal.These findings were supported by robust checks.This study offers theoretical insights and empirical evidence that support the coordinated development of digital government and the digital factor market,as well as business environment reforms that are in alignment with the innovation demands of the digital era.
基金Project(ASM-20240)supported by the Key Laboratory of Advanced Structural Materials(Changchun University of Technology),Ministry of Education,ChinaProject(2022TD-30)supported by the Scientific and Technological Innovation Team Project of Shaanxi Innovation Capability Support Plan,China。
文摘This work examines the microstructure and corrosion properties of fine-grained Al 7075 across different regions under varying cooling conditions during friction stir welding.The findings demonstrate that forced cooling significantly improves the corrosion resistance of the welded joints.Specifically,the corrosion resistance was the highest in the stir zone,followed by the thermo-mechanical affected zone,and then the heat affected zone.Forced cooling mitigates grain growth by controlling the welding thermal effects,thereby increasing the proportion ofΣ3 grain boundaries.The modification of these microstructural characteristics promotes the formation of a dense oxide layer,thereby enhancing the corrosion resistance.Furthermore,forced cooling mitigates the precipitation and coarsening of the anodic phase in the stir zone,which in turn reduces the susceptibility of the joint to pitting corrosion.Additionally,the lower recrystallization texture content in the joint,resulting from forced cooling,contributes to a reduction in the number of corrosion-active sites,thereby further improving the corrosion performance of the welded joint.
基金supported by the National Natural Science Foundation of China(No.51706105)。
文摘Al/NH_(4)CoF_(3)-Φ(Φ=0.5,1.0,1.5,2.0,and 3.0)binary composites and Al-NH_(4)CoF_(3)@P(VDF-HFP)ternary composites are fabricated via ultrasonication-assisted blending and electrostatic spraying.The effect of equivalence ratio(Φ)on the reaction properties is systematically investigated in the binary Al/NH_(4)CoF_(3)system.For ternary systems,electrostatic spraying allows both components to be efficiently encapsulated by P(VDF-HFP)and to achieve structural stabilization and enhanced reactivity through synergistic interfacial interactions.Morphological analysis using SEM/TEM revealed that P(VDF-HFP)formed a protective layer on Al and NH_(4)CoF_(3)particles,improving dispersion,hydrophobicity(water contact angle increased by 80.5%compared to physically mixed composites),and corrosion resistance.Thermal decomposition of NH_(4)CoF_(3)occurred at 265℃,releasing NH_(3)and HF,which triggered exothermic reactions with Al.The ternary composites exhibited a narrowed main reaction temperature range and concentrated heat release,attributed to improved interfacial contact and polymer decomposition.Combustion tests demonstrated that Al-NH_(4)CoF_(3)@P(VDF-HFP)achieved self-sustaining combustion.In addition,a simple validation was done by replacing the Al component in the aluminium-containing propellant,demonstrating its potential application in the propellant field.This work establishes a novel strategy for designing stable,high-energy composites with potential applications in advanced propulsion systems.
文摘Isolation technology can reduce the type of structural damage that earthquakes cause.A new type of composite sliding-rolling friction composite seismic isolation bearing(SRF)with composite sliding friction and rolling friction is proposed.SRF is capable of realizing a parallel arrangement of sliding friction and rolling friction,and the coefficient of dynamic friction shows variability.The proposed static tests on composite bearings were conducted to investigate the effects of the number of shims,loading speed and vertical pressure on the dynamic friction factor.Test results show that the coefficient of dynamic friction first generally decreases and then increases with an increase in sliding speed,prior to again decreasing with an increase in vertical pressure.The dynamic friction factor increases and then decreases with an increase in the number of shims for a four-roll ball.It decreases and then increases with an increase in the number of shims for a five-roll ball.Based on finite element analysis,modeling and analyzing the effects of the coefficient of friction,the number of balls and the number of shims on the hysteresis performance of the support and derive its skeleton curve.The SRF hysteretic performance,dynamic friction factor and the number of rolling balls and shims show significant correlation.
基金supported and funded by the National Key Research and Development Program of China(2023YFD1300801)the Agricultural Science and Technology Innovation Program in Chinese Academy of Agricultural Sciences(ASTIP-IAS-08)。
文摘Background The decline in reproductive performance of aged hens is mainly attributed to oxidative damage in reproductive organs,hepatic lipid metabolism disorders,and intestinal microbiota dysbiosis.Glycyrrhizin(GL)has been proven to enhance antioxidant capacity,regulate lipid metabolism and gut microbiota in mammals,but its efficacy in hens remains unclear.Hence,this study aimed to investigate whether dietary GL supplementation improves reproductive performance in hens during the late laying stage by modulating intestinal microbiota composition,hepatic lipid metabolism and ovarian antioxidant status.Results Dietary supplementation with 100 mg/kg GL significantly improved the egg production rate,egg quality,and hatching rate in aged breeder hens(P<0.05).GL supplementation also increased the serum levels of HDLC,TP and ALB,and enhanced the antioxidant capacity in both serum and ovary(P<0.05).In addition,dietary GL elevated the serum progesterone(P4)levels by enhancing the transcription level of steroid synthesis key enzymes(CYP11A1 and 3β-HSD)in the ovary(P<0.05).Dietary GL also promoted the synthesis and transport of vitellogenin(VTG)by upregulating the VTG-Ⅱ(P<0.05)and APOV1(P=0.077)expression levels in the liver,thereby increasing the number of grade follicles and small yellow follicles.Moreover,dietary GL enhanced hepatic fatty acidβ-oxidation by upregulating PPARαand CPT-I(P<0.05),and downregulating ACC expression levels(P<0.05).In agreement,liver metabolomics analysis revealed that dietary GL supplementation significantly altered hepatic metabolism,with 389 differentially identified metabolites(P<0.05).The key metabolites(e.g.,taurocholic acid,tauroursodeoxycholic acid,nicotinuric acid,glycodeoxycholic acid(hydrate))were identified,and they were mainly functionally enriched in betaalanine metabolism nicotinate,taurine and hypotaurine metabolism(P<0.05).Finally,16S rRNA gene sequencing revealed that dietary GL reversed age-induced changes in gut microbiota composition,characterized by a significant increase in Lactobacillus abundance and a decrease in Bacteroides(P<0.05).Conclusions These results collectively demonstrate that dietary supplementation with 100 mg/kg GL improved reproductive performance by reversing age-induced changes in gut microbiota,enhancing hepatic vitellogenin synthesis,and ameliorating ovarian function in aged breeder hens.This study suggests that dietary GL is a potential strategy to improve reproductive performance in broiler breeder hens during the late laying period.
基金supported by the National Natural Science Foundation of China(Grant No.12402268)the Fundamental Research Funds for the Central Universities(Grant No.30925010410)。
文摘The core components of an aircraft and the source of its lift are its wings,but lift generation is disrupted by the high temperature and pressure generated on the wing surface when an aircraft gun is fired.Here,to investigate how this process influences the aerodynamic parameters of aircraft wings,the k-ωshearstress-transport turbulence model and the nested dynamic grid technique are used to analyze numerically the transient process of the muzzle jet of a 30-mm small-caliber aircraft gun in highaltitude(10 km)flight with an incoming Mach number of Ma=0.8.For comparison,two other models are established,one with no projectile and the other with no wing.The results indicate that when the aircraft gun is fired,the muzzle jet acts on the wing,creating a pressure field thereon.The uneven distribution of high pressure greatly reduces the lift of the aircraft,causing oscillations in its drag and disrupting its dynamic balance,thereby affecting its flight speed and attitude.Meanwhile,the muzzle jet is obstructed by the wing,and its flow field is distorted and deformed,developing upward toward the wing.Because of the influence of the incoming flow,the shockwave front of the projectile changes from a smooth spherical shape to an irregular one,and the motion parameters of the projectile are also greatly affected by oscillations.The present results provide an important theoretical basis for how the guns of fighter aircraft influence the aerodynamic performance of the wings.
基金supported by the Jiangsu Engineering Research Center of the Key Technology for Intelligent Manufacturing Equipment and the Suqian Key Laboratory of Intelligent Manufacturing(Grant No.M202108).
文摘To address the issues of insufficient and imbalanced data samples in proton exchange membrane fuel cell(PEMFC)performance degradation prediction,this study proposes a data augmentation-based model to predict PEMFC performance degradation.Firstly,an improved generative adversarial network(IGAN)with adaptive gradient penalty coefficient is proposed to address the problems of excessively fast gradient descent and insufficient diversity of generated samples.Then,the IGANis used to generate datawith a distribution analogous to real data,therebymitigating the insufficiency and imbalance of original PEMFC samples and providing the predictionmodel with training data rich in feature information.Finally,a convolutional neural network-bidirectional long short-termmemory(CNN-BiLSTM)model is adopted to predict PEMFC performance degradation.Experimental results show that the data generated by the proposed IGAN exhibits higher quality than that generated by the original GAN,and can fully characterize and enrich the original data’s features.Using the augmented data,the prediction accuracy of the CNN-BiLSTM model is significantly improved,rendering it applicable to tasks of predicting PEMFC performance degradation.
基金supported and funded by theDeanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2503).
文摘In recent years,fog computing has become an important environment for dealing with the Internet of Things.Fog computing was developed to handle large-scale big data by scheduling tasks via cloud computing.Task scheduling is crucial for efficiently handling IoT user requests,thereby improving system performance,cost,and energy consumption across nodes in cloud computing.With the large amount of data and user requests,achieving the optimal solution to the task scheduling problem is challenging,particularly in terms of cost and energy efficiency.In this paper,we develop novel strategies to save energy consumption across nodes in fog computing when users execute tasks through the least-cost paths.Task scheduling is developed using modified artificial ecosystem optimization(AEO),combined with negative swarm operators,Salp Swarm Algorithm(SSA),in order to competitively optimize their capabilities during the exploitation phase of the optimal search process.In addition,the proposed strategy,Enhancement Artificial Ecosystem Optimization Salp Swarm Algorithm(EAEOSSA),attempts to find the most suitable solution.The optimization that combines cost and energy for multi-objective task scheduling optimization problems.The backpack problem is also added to improve both cost and energy in the iFogSim implementation as well.A comparison was made between the proposed strategy and other strategies in terms of time,cost,energy,and productivity.Experimental results showed that the proposed strategy improved energy consumption,cost,and time over other algorithms.Simulation results demonstrate that the proposed algorithm increases the average cost,average energy consumption,and mean service time in most scenarios,with average reductions of up to 21.15%in cost and 25.8%in energy consumption.
基金supported by the Science and Technology Research and Development Program Project of China Railway Group Limited (Grant No.2022-Major-17)the National Natural Science Foundation of China (Grant Nos.52578619,52178180)+2 种基金the National Key Research and Development Program of China (Grant No.2022YFC3004304)the Frontier Cross Research Project of Central South University (Grant No.2023QYJC006)the Natural Science Foundation of Hunan Province Funding Project (Grant No.2023JJ40724)。
文摘Under earthquake action, different site conditions have a notable impact on the dynamic response of high-speed railway bridges after earthquakes, which in turn poses a threat to the running stability of trains in the post-earthquake period. Therefore, establishing a calculation method for the post-earthquake train speed threshold that considers the influence of different site characteristics is of great engineering significance. Taking the CRTS Ⅲ slab track as the research object, this study is based on the track irregularity root mean square rate(TRR), which the authors proposed earlier to quantify the track regularity level. Using the nonlinear least squares fitting method, the mapping relationship between the TRR and the postearthquake train running performance indicators on bridges is established. Furthermore, the influence of laws governing site categories and train speeds on post-earthquake train running performance on bridges is analyzed, and a train speed threshold for bridges based on running performance under random site conditions is proposed. The research results indicate that all train running performance indicators increase significantly with the increase of train operating speed;different site categories have a significant impact on post-earthquake track residual deformation and train running stability. The greater the amplitude of postearthquake track alignment residual deformation, the lower the threshold for the stable running speed of trains after the earthquake, with the speed threshold decreasing by up to 20%. The research outcomes can provide technical references for the post-earthquake safe operation and maintenance of high-speed railway bridges under complex site conditions, as well as the formulation of targeted train speed control schemes.
