In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapi...In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapid deployment and high mobil-ity,are commonly regarded as an ideal option for con-structing temporary communication networks.Con-sidering the limited computing capability and battery power of UAVs,this paper proposes a two-layer UAV cooperative computing offloading strategy for emer-gency disaster relief scenarios.The multi-agent twin delayed deep deterministic policy gradient(MATD3)algorithm integrated with prioritized experience replay(PER)is utilized to jointly optimize the scheduling strategies of UAVs,task offloading ratios,and their mobility,aiming to diminish the energy consumption and delay of the system to the minimum.In order to address the aforementioned non-convex optimiza-tion issue,a Markov decision process(MDP)has been established.The results of simulation experiments demonstrate that,compared with the other four base-line algorithms,the algorithm introduced in this paper exhibits better convergence performance,verifying its feasibility and efficacy.展开更多
Hydrogen fuel cell ships are one of the key solutions to achieving zero carbon emissions in shipping.Multi-fuel cell stacks(MFCS)systems are frequently employed to fulfill the power requirements of high-load power equ...Hydrogen fuel cell ships are one of the key solutions to achieving zero carbon emissions in shipping.Multi-fuel cell stacks(MFCS)systems are frequently employed to fulfill the power requirements of high-load power equipment on ships.Compared to single-stack system,MFCS may be difficult to apply traditional energy management strategies(EMS)due to their complex structure.In this paper,a two-layer power allocation strategy for MFCS of a hydrogen fuel cell ship is proposed to reduce the complexity of the allocation task by splitting it into each layer of the EMS.The first layer of the EMSis centered on the Nonlinear Model Predictive Control(NMPC).The Northern Goshawk Optimization(NGO)algorithm is used to solve the nonlinear optimization problem in NMPC,and the local fine search is performed using sequential quadratic programming(SQP).Based on the power allocation results of the first layer,the second layer is centered on a fuzzy rule-based adaptive power allocation strategy(AP-Fuzzy).The membership function bounds of the fuzzy controller are related to the aging level of the MFCS.The Particle Swarm Optimization(PSO)algorithm is used to optimize the parameters of the residual membership function to improve the performance of the proposed strategy.The effectiveness of the proposed EMS is verified by comparing it with the traditional EMS.The experimental results show that the EMS proposed in this paper can ensure reasonable hydrogen consumption,slow down the FC aging and equalize its performance,effectively extend the system life,and ensure that the ship has good endurance after completing the mission.展开更多
Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered so...Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.展开更多
We study evolutionary games in two-layer networks by introducing the correlation between two layers through the C-dominance or the D-dominance. We assume that individuals play prisoner＇s dilemma game （PDG） in one l...We study evolutionary games in two-layer networks by introducing the correlation between two layers through the C-dominance or the D-dominance. We assume that individuals play prisoner＇s dilemma game （PDG） in one layer and snowdrift game （SDG） in the other. We explore the dependences of the fraction of the strategy cooperation in different layers on the game parameter and initial conditions. The results on two-layer square lattices show that, when cooperation is the dominant strategy, initial conditions strongly influence cooperation in the PDG layer while have no impact in the SDG layer. Moreover, in contrast to the result for PDG in single-layer square lattices, the parameter regime where cooperation could be maintained expands significantly in the PDG layer. We also investigate the effects of mutation and network topology. We find that different mutation rates do not change the cooperation behaviors. Moreover, similar behaviors on cooperation could be found in two-layer random networks.展开更多
To address the frequency fluctuation problem caused by the power dynamic imbalance between the power system and the loadwhen a large number of newenergy sources are connected to the grid,a two-layer fuzzy control stra...To address the frequency fluctuation problem caused by the power dynamic imbalance between the power system and the loadwhen a large number of newenergy sources are connected to the grid,a two-layer fuzzy control strategy is proposed for the participation of the energy storage battery system in FM.Firstly,considering the coordination of FM units responding to automatic power generation control commands,a comprehensive allocation strategy of two signals under automatic power generation control commands is proposed to give full play to the advantages of two FM signals while enabling better coordination of two FM units responding to FM commands;secondly,based on the grid FM demand and battery FM capability,a double-layer fuzzy control strategy is proposed for FM units responding to automatic power generation control commands in a coordinated manner under dual-signal allocation mode to precisely allocate the power output depth of FM units,which can control the fluctuation of frequency deviation within a smaller range at a faster speed while maintaining the battery charge state;finally,the proposed Finally,the proposed control strategy is simulated and verified inMatlab/Simulink.The results show that the proposed control strategy can control the frequency deviation within a smaller range in a shorter time,better stabilize the fluctuation of the battery charge level,and improve the utilization of the FM unit.展开更多
In Information Centric Networking(ICN)where content is the object of exchange,in-network caching is a unique functional feature with the ability to handle data storage and distribution in remote sensing satellite netw...In Information Centric Networking(ICN)where content is the object of exchange,in-network caching is a unique functional feature with the ability to handle data storage and distribution in remote sensing satellite networks.Setting up cache space at any node enables users to access data nearby,thus relieving the processing pressure on the servers.However,the existing caching strategies still suffer from the lack of global planning of cache contents and low utilization of cache resources due to the lack of fine-grained division of cache contents.To address the issues mentioned,a cooperative caching strategy(CSTL)for remote sensing satellite networks based on a two-layer caching model is proposed.The two-layer caching model is constructed by setting up separate cache spaces in the satellite network and the ground station.Probabilistic caching of popular contents in the region at the ground station to reduce the access delay of users.A content classification method based on hierarchical division is proposed in the satellite network,and differential probabilistic caching is employed for different levels of content.The cached content is also dynamically adjusted by analyzing the subsequent changes in the popularity of the cached content.In the two-layer caching model,ground stations and satellite networks collaboratively cache to achieve global planning of cache contents,rationalize the utilization of cache resources,and reduce the propagation delay of remote sensing data.Simulation results show that the CSTL strategy not only has a high cache hit ratio compared with other caching strategies but also effectively reduces user request delay and server load,which satisfies the timeliness requirement of remote sensing data transmission.展开更多
This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerge...This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerged cylindrical buoy.The system is modeled as a two-layer fluid with infinite horizontal extent and finite depth.The radiation problem is analyzed in the context of linear water waves.The fluid domain is divided into outer and inner zones,and mathematical solutions for the pitch radiating potential are derived for the corresponding boundary valve problem in these zones using the separation of variables approach.Using the matching eigenfunction expansion method,the unknown coefficients in the analytical expression of the radiation potentials are evaluated.The resulting radiation potential is then used to compute the added mass and damping coefficients.Several numerical results for the added mass and damping coefficients are investigated for numerous parameters,particularly the effects of the cylinder radius,the draft of the submerged cylinder,and the density proportion between the two fluid layers across different frequency ranges.The major findings are presented and discussed.展开更多
Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class at...Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class attacks,this study proposes an intrusion detection method based on a two-layer structure.The first layer employs a CNN-BiLSTM model incorporating an attention mechanism to classify network traffic into normal traffic,majority class attacks,and merged minority class attacks.The second layer further segments the minority class attacks through Stacking ensemble learning.The datasets are selected from the generic network dataset CIC-IDS2017,NSL-KDD,and the industrial network dataset Mississippi Gas Pipeline dataset to enhance the generalization and practical applicability of the model.Experimental results show that the proposed model achieves an overall detection accuracy of 99%,99%,and 95%on the CIC-IDS2017,NSL-KDD,and industrial network datasets,respectively.It also significantly outperforms traditional methods in terms of detection accuracy and recall rate for minority class attacks.Compared with the single-layer deep learning model,the two-layer structure effectively reduces the false alarm rate while improving the minority-class attack detection performance.The research in this paper not only improves the adaptability of NIDS to complex network environments but also provides a new solution for minority-class attack detection in industrial network security.展开更多
This article focuses on the challenges of rural economic development under the strategy of rural revitalization,and deeply analyzes the current situation of rural economic development.Research has found that although ...This article focuses on the challenges of rural economic development under the strategy of rural revitalization,and deeply analyzes the current situation of rural economic development.Research has found that although the rural revitalization strategy has achieved significant results in improving residents’quality of life,promoting agricultural modernization,it still faces challenges such as severe loss of human resources,insufficient agricultural technological innovation,and backward infrastructure construction.In response to these challenges,this paper proposes optimization strategies from three aspects:strengthening rural education and talent team construction,promoting agricultural technology innovation and achievement transformation,and increasing investment in rural infrastructure construction.展开更多
Ischemic stroke is a major cause of neurological deficits and high disability rate.As the primary immune cells of the central nervous system,microglia play dual roles in neuroinflammation and tissue repair following a...Ischemic stroke is a major cause of neurological deficits and high disability rate.As the primary immune cells of the central nervous system,microglia play dual roles in neuroinflammation and tissue repair following a stroke.Their dynamic activation and polarization states are key factors that influence the disease process and treatment outcomes.This review article investigates the role of microglia in ischemic stroke and explores potential intervention strategies.Microglia exhibit a dynamic functional state,transitioning between pro-inflammatory(M1)and anti-inflammatory(M2)phenotypes.This duality is crucial in ischemic stroke,as it maintains a balance between neuroinflammation and tissue repair.Activated microglia contribute to neuroinflammation through cytokine release and disruption of the blood-brain barrier,while simultaneously promoting tissue repair through anti-inflammatory responses and regeneration.Key pathways influencing microglial activation include Toll-like receptor 4/nuclear factor kappa B,mitogen-activated protein kinases,Janus kinase/signal transducer and activator of transcription,and phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin pathways.These pathways are targets for various experimental therapies aimed at promoting M2 polarization and mitigating damage.Potential therapeutic agents include natural compounds found in drugs such as minocycline,as well as traditional Chinese medicines.Drugs that target these regulatory mechanisms,such as small molecule inhibitors and components of traditional Chinese medicines,along with emerging technologies such as single-cell RNA sequencing and spatial transcriptomics,offer new therapeutic strategies and clinical translational potential for ischemic stroke.展开更多
BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To ...BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To develop an interpretable noninvasive early diagnostic model for PDAC using plasma extracellular vesicle long RNA(EvlRNA).METHODS The diagnostic model was constructed based on plasma EvlRNA data.During the process of establishing the model,EvlRNA-index was introduced,and four algorithms were adopted to calculate EvlRNA-index.After the model was successfully constructed,performance evaluation was conducted.A series of bioinformatics methods were adopted to explore the potential mechanism of EvlRNA-index as the input feature of the model.And the relationship between key characteristics and PDAC were explored at the single-cell level.RESULTS A novel interpretable machine learning framework was developed based on plasma EvlRNA.In this framework,a two-layer classifier was established.A new concept was proposed:EvlRNA-index.Based on EvlRNA-index,a cancer diagnostic model was established,and a good diagnostic effect was achieved.The accuracy of PDACandCPvsHealth-Probabilistic PCA Index-SVM(PDAC and chronic pancreatitis vs health-probabilistic principal component analysis index-support vector machine)(1-18)was 91.51%,with Mathew’s correlation coefficient 0.7760 and area under the curve 0.9560.In the second layer of the model,the accuracy of PDACvsCP-Probabilistic PCA Index-RF(PDAC vs chronic pancreatitis-probabilistic principal component analysis index-random forest)(2-17)was 93.83%,with Mathew’s correlation coefficient 0.8422 and area under the curve 0.9698.Forty-nine PDAC-related genes were identified,among which 16 were known,inferring that the remaining ones were also PDAC-related genes.CONCLUSION An interpretable two-layer machine learning framework was proposed for early diagnosis and prediction of PDAC based on plasma EvlRNA,providing new insights into the clinical value of EvlRNA.展开更多
Dove’s 2017 advertising incident,which sparked widespread debate regarding perceived cultural insensitivity,highlighted a disconnect between the brand’s“Real Beauty”positioning and public reception.In response,thi...Dove’s 2017 advertising incident,which sparked widespread debate regarding perceived cultural insensitivity,highlighted a disconnect between the brand’s“Real Beauty”positioning and public reception.In response,this study proposes a strategic digital recovery framework,including revised campaign content,transparent communication through social media,and data-driven customer segmentation based on diverse skincare needs and cultural backgrounds.A PESTLE analysis underscores the importance of digital transformation and rising social consciousness in brand management.Findings suggest that inclusive messaging,precision targeting,and omnichannel digital engagement are key to restoring brand trust and reputation in the digital landscape.展开更多
In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the oper...In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the operational characteristics of rural microgrids and their impact on users,this paper establishes a two-layer scheduling model incorporating flexible loads.The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid,while the lower-layer aims to minimize the total electricity cost for rural users.An Improved Adaptive Genetic Algorithm(IAGA)is proposed to solve the model.Results show that the two-layer scheduling model with flexible loads can effectively smooth load fluctuations,enhance microgrid stability,increase clean energy consumption,and balance microgrid operating costs with user benefits.展开更多
Neural injuries can cause considerable functional impairments,and both central and peripheral nervous systems have limited regenerative capacity.The existing conventional pharmacological treatments in clinical practic...Neural injuries can cause considerable functional impairments,and both central and peripheral nervous systems have limited regenerative capacity.The existing conventional pharmacological treatments in clinical practice show poor targeting,rapid drug clearance from the circulatory system,and low therapeutic efficiency.Therefore,in this review,we have first described the mechanisms underlying nerve regeneration,characterized the biomaterials used for drug delivery to facilitate nerve regeneration,and highlighted the functionalization strategies used for such drug-delivery systems.These systems mainly use natural and synthetic polymers,inorganic materials,and hybrid systems with advanced drug-delivery abilities,including nanoparticles,hydrogels,and scaffoldbased systems.Then,we focused on comparing the types of drug-delivery systems for neural regeneration as well as the mechanisms and challenges associated with targeted delivery of drugs to facilitate neural regeneration.Finally,we have summarized the clinical application research and limitations of targeted delivery of these drugs.These biomaterials and drug-delivery systems can provide mechanical support,sustained release of bioactive molecules,and enhanced intercellular contact,ultimately reducing cell apoptosis and enhancing functional recovery.Nevertheless,immune reactions,degradation regulation,and clinical translations remain major unresolved challenges.Future studies should focus on optimizing biomaterial properties,refining delivery precision,and overcoming translational barriers to advance these technologies toward clinical applications.展开更多
Using photoelectrocatalytic CO_(2) reduction reaction(CO_(2)RR)to produce valuable fuels is a fascinating way to alleviate environmental issues and energy crises.Bismuth-based(Bi-based)catalysts have attracted widespr...Using photoelectrocatalytic CO_(2) reduction reaction(CO_(2)RR)to produce valuable fuels is a fascinating way to alleviate environmental issues and energy crises.Bismuth-based(Bi-based)catalysts have attracted widespread attention for CO_(2)RR due to their high catalytic activity,selectivity,excellent stability,and low cost.However,they still need to be further improved to meet the needs of industrial applications.This review article comprehensively summarizes the recent advances in regulation strategies of Bi-based catalysts and can be divided into six categories:(1)defect engineering,(2)atomic doping engineering,(3)organic framework engineering,(4)inorganic heterojunction engineering,(5)crystal face engineering,and(6)alloying and polarization engineering.Meanwhile,the corresponding catalytic mechanisms of each regulation strategy will also be discussed in detail,aiming to enable researchers to understand the structure-property relationship of the improved Bibased catalysts fundamentally.Finally,the challenges and future opportunities of the Bi-based catalysts in the photoelectrocatalytic CO_(2)RR application field will also be featured from the perspectives of the(1)combination or synergy of multiple regulatory strategies,(2)revealing formation mechanism and realizing controllable synthesis,and(3)in situ multiscale investigation of activation pathways and uncovering the catalytic mechanisms.On the one hand,through the comparative analysis and mechanism explanation of the six major regulatory strategies,a multidimensional knowledge framework of the structure-activity relationship of Bi-based catalysts can be constructed for researchers,which not only deepens the atomic-level understanding of catalytic active sites,charge transport paths,and the adsorption behavior of intermediate products,but also provides theoretical guiding principles for the controllable design of new catalysts;on the other hand,the promising collaborative regulation strategies,controllable synthetic paths,and the in situ multiscale characterization techniques presented in this work provides a paradigm reference for shortening the research and development cycle of high-performance catalysts,conducive to facilitating the transition of photoelectrocatalytic CO_(2)RR technology from the laboratory routes to industrial application.展开更多
This paper addresses a target-enclosing problem for multiple spacecraft systems by proposing a two-layer affine formation control strategy. Compared with the existing methods,the adopted two-layer network structure in...This paper addresses a target-enclosing problem for multiple spacecraft systems by proposing a two-layer affine formation control strategy. Compared with the existing methods,the adopted two-layer network structure in this paper is generally directed, which is suitable for practical space missions. Firstly, distributed finite-time sliding-mode estimators and formation controllers in both layers are designed separately to improve the flexibility of the formation control system. By introducing the properties of affine transformation into formation control protocol design,the controllers can be used to track different time-varying target formation patterns. Besides, multilayer time-varying encirclements can be achieved with particular shapes to surround the moving target. In the sequel, by integrating adaptive neural networks and specialized artificial potential functions into backstepping controllers, the problems of uncertain Euler-Lagrange models, collision avoidance as well as formation reconfiguration are solved simultaneously. The stability of the proposed controllers is verified by the Lyapunov direct method. Finally, two simulation examples of triangle formation and more complex hexagon formation are presented to illustrate the feasibility of the theoretical results.展开更多
Based on the synchronous joint gravity and magnetic inversion of single interface by Pilkington and the need of revealing Cenozoic and crystalline basement thickness in the new round of oil-gas exploration, we propose...Based on the synchronous joint gravity and magnetic inversion of single interface by Pilkington and the need of revealing Cenozoic and crystalline basement thickness in the new round of oil-gas exploration, we propose a joint gravity and magnetic inversion methodfor two-layer models by concentrating on the relationship between the change of thicknessI and position of the middle layer and anomaly and discuss the effects of the key parameters. Model tests and application to field data show the validity of this method.展开更多
A model is proposed to evaluate the,effective modufi of a composite reinforced by two-layered spherical inclusions.This model is based on the localisation problem of a two- layered spherical inclusion embedded in an i...A model is proposed to evaluate the,effective modufi of a composite reinforced by two-layered spherical inclusions.This model is based on the localisation problem of a two- layered spherical inclusion embedded in an infinite matrix.The interations of the reinforced phases are taken into account by using the average matrix stress concept.When the external layer vanishes,the proposed model reduces to the classical Mori-Tanaka's model for spherical inclusions.Theoretical results for the composite of polyester matrix filled by hollow glass spheres and voids show excellent agreement with experimental results.展开更多
Many rock avalanches were triggered by the Wenchuan earthquake on May 12, 2008 in southwest China. Protection galleries covered with a single soil layer are usually used to protect against rockfall. Since one-layer pr...Many rock avalanches were triggered by the Wenchuan earthquake on May 12, 2008 in southwest China. Protection galleries covered with a single soil layer are usually used to protect against rockfall. Since one-layer protection galleries do not have sufficient buffer capacity, a two-layered absorbing system has been designed. This study aims to find whether an expanded poly-styrol （EPS） cushion, which is used in the soil-covered protection galleries for shock absorption, could be positioned under dynamic loadings. The dynamic impacts of the two-layered absorbing system under the conditions of rock avalanches are numerically simulated through a 2D discrete dement method. By selecting reasonable parameters, a series of numerical experiments were conducted to find the best combination for the two- layered absorbing system. The values of the EPS layer area as a percentage of the total area were set as 0% （Sl）, 22~ （S2）, and 70% （$3）. 22~ of the area of the EPS layer was found to be a reasonable value, and experiments were conducted to find the best position of the EPS layer in the two-layered absorbing system. The numerical results yield useful conclusions regarding the interaction between the impacting avalanches and the two-layered absorbing system. The soil layer can absorb the shock energy effectively and S2 （0.4-m thick EPS cushion covered with soil layer） is the most efficient combination, which can reduce the impact force, compared with the other combinations.展开更多
基金supported by the Basic Scientific Research Business Fund Project of Higher Education Institutions in Heilongjiang Province(145409601)the First Batch of Experimental Teaching and Teaching Laboratory Construction Research Projects in Heilongjiang Province(SJGZ20240038).
文摘In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapid deployment and high mobil-ity,are commonly regarded as an ideal option for con-structing temporary communication networks.Con-sidering the limited computing capability and battery power of UAVs,this paper proposes a two-layer UAV cooperative computing offloading strategy for emer-gency disaster relief scenarios.The multi-agent twin delayed deep deterministic policy gradient(MATD3)algorithm integrated with prioritized experience replay(PER)is utilized to jointly optimize the scheduling strategies of UAVs,task offloading ratios,and their mobility,aiming to diminish the energy consumption and delay of the system to the minimum.In order to address the aforementioned non-convex optimiza-tion issue,a Markov decision process(MDP)has been established.The results of simulation experiments demonstrate that,compared with the other four base-line algorithms,the algorithm introduced in this paper exhibits better convergence performance,verifying its feasibility and efficacy.
基金supported by the National Key R&D Program of China(2022YFB4301403).
文摘Hydrogen fuel cell ships are one of the key solutions to achieving zero carbon emissions in shipping.Multi-fuel cell stacks(MFCS)systems are frequently employed to fulfill the power requirements of high-load power equipment on ships.Compared to single-stack system,MFCS may be difficult to apply traditional energy management strategies(EMS)due to their complex structure.In this paper,a two-layer power allocation strategy for MFCS of a hydrogen fuel cell ship is proposed to reduce the complexity of the allocation task by splitting it into each layer of the EMS.The first layer of the EMSis centered on the Nonlinear Model Predictive Control(NMPC).The Northern Goshawk Optimization(NGO)algorithm is used to solve the nonlinear optimization problem in NMPC,and the local fine search is performed using sequential quadratic programming(SQP).Based on the power allocation results of the first layer,the second layer is centered on a fuzzy rule-based adaptive power allocation strategy(AP-Fuzzy).The membership function bounds of the fuzzy controller are related to the aging level of the MFCS.The Particle Swarm Optimization(PSO)algorithm is used to optimize the parameters of the residual membership function to improve the performance of the proposed strategy.The effectiveness of the proposed EMS is verified by comparing it with the traditional EMS.The experimental results show that the EMS proposed in this paper can ensure reasonable hydrogen consumption,slow down the FC aging and equalize its performance,effectively extend the system life,and ensure that the ship has good endurance after completing the mission.
文摘Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11575036,71301012,and 11505016
文摘We study evolutionary games in two-layer networks by introducing the correlation between two layers through the C-dominance or the D-dominance. We assume that individuals play prisoner＇s dilemma game （PDG） in one layer and snowdrift game （SDG） in the other. We explore the dependences of the fraction of the strategy cooperation in different layers on the game parameter and initial conditions. The results on two-layer square lattices show that, when cooperation is the dominant strategy, initial conditions strongly influence cooperation in the PDG layer while have no impact in the SDG layer. Moreover, in contrast to the result for PDG in single-layer square lattices, the parameter regime where cooperation could be maintained expands significantly in the PDG layer. We also investigate the effects of mutation and network topology. We find that different mutation rates do not change the cooperation behaviors. Moreover, similar behaviors on cooperation could be found in two-layer random networks.
基金funded by the Gansu Provincial Science and Technology Information Disclosure System Project(21ZD8JA001)Tianyou Innovation Team of Lanzhou Jiaotong University(TY202009).
文摘To address the frequency fluctuation problem caused by the power dynamic imbalance between the power system and the loadwhen a large number of newenergy sources are connected to the grid,a two-layer fuzzy control strategy is proposed for the participation of the energy storage battery system in FM.Firstly,considering the coordination of FM units responding to automatic power generation control commands,a comprehensive allocation strategy of two signals under automatic power generation control commands is proposed to give full play to the advantages of two FM signals while enabling better coordination of two FM units responding to FM commands;secondly,based on the grid FM demand and battery FM capability,a double-layer fuzzy control strategy is proposed for FM units responding to automatic power generation control commands in a coordinated manner under dual-signal allocation mode to precisely allocate the power output depth of FM units,which can control the fluctuation of frequency deviation within a smaller range at a faster speed while maintaining the battery charge state;finally,the proposed Finally,the proposed control strategy is simulated and verified inMatlab/Simulink.The results show that the proposed control strategy can control the frequency deviation within a smaller range in a shorter time,better stabilize the fluctuation of the battery charge level,and improve the utilization of the FM unit.
基金This research was funded by the National Natural Science Foundation of China(No.U21A20451)the Science and Technology Planning Project of Jilin Province(No.20200401105GX)the China University Industry University Research Innovation Fund(No.2021FNA01003).
文摘In Information Centric Networking(ICN)where content is the object of exchange,in-network caching is a unique functional feature with the ability to handle data storage and distribution in remote sensing satellite networks.Setting up cache space at any node enables users to access data nearby,thus relieving the processing pressure on the servers.However,the existing caching strategies still suffer from the lack of global planning of cache contents and low utilization of cache resources due to the lack of fine-grained division of cache contents.To address the issues mentioned,a cooperative caching strategy(CSTL)for remote sensing satellite networks based on a two-layer caching model is proposed.The two-layer caching model is constructed by setting up separate cache spaces in the satellite network and the ground station.Probabilistic caching of popular contents in the region at the ground station to reduce the access delay of users.A content classification method based on hierarchical division is proposed in the satellite network,and differential probabilistic caching is employed for different levels of content.The cached content is also dynamically adjusted by analyzing the subsequent changes in the popularity of the cached content.In the two-layer caching model,ground stations and satellite networks collaboratively cache to achieve global planning of cache contents,rationalize the utilization of cache resources,and reduce the propagation delay of remote sensing data.Simulation results show that the CSTL strategy not only has a high cache hit ratio compared with other caching strategies but also effectively reduces user request delay and server load,which satisfies the timeliness requirement of remote sensing data transmission.
基金supported by MHRD as researcher C.K.Neog received the MHRD Institute GATE scholarship from Govt.of India.
文摘This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerged cylindrical buoy.The system is modeled as a two-layer fluid with infinite horizontal extent and finite depth.The radiation problem is analyzed in the context of linear water waves.The fluid domain is divided into outer and inner zones,and mathematical solutions for the pitch radiating potential are derived for the corresponding boundary valve problem in these zones using the separation of variables approach.Using the matching eigenfunction expansion method,the unknown coefficients in the analytical expression of the radiation potentials are evaluated.The resulting radiation potential is then used to compute the added mass and damping coefficients.Several numerical results for the added mass and damping coefficients are investigated for numerous parameters,particularly the effects of the cylinder radius,the draft of the submerged cylinder,and the density proportion between the two fluid layers across different frequency ranges.The major findings are presented and discussed.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)—Innovative Human Resource Development for Local Intellectualization program grant funded by the Korea government(MSIT)(IITP-2025-RS-2022-00156334)in part by Liaoning Province Nature Fund Project(2024-BSLH-214).
文摘Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class attacks,this study proposes an intrusion detection method based on a two-layer structure.The first layer employs a CNN-BiLSTM model incorporating an attention mechanism to classify network traffic into normal traffic,majority class attacks,and merged minority class attacks.The second layer further segments the minority class attacks through Stacking ensemble learning.The datasets are selected from the generic network dataset CIC-IDS2017,NSL-KDD,and the industrial network dataset Mississippi Gas Pipeline dataset to enhance the generalization and practical applicability of the model.Experimental results show that the proposed model achieves an overall detection accuracy of 99%,99%,and 95%on the CIC-IDS2017,NSL-KDD,and industrial network datasets,respectively.It also significantly outperforms traditional methods in terms of detection accuracy and recall rate for minority class attacks.Compared with the single-layer deep learning model,the two-layer structure effectively reduces the false alarm rate while improving the minority-class attack detection performance.The research in this paper not only improves the adaptability of NIDS to complex network environments but also provides a new solution for minority-class attack detection in industrial network security.
文摘This article focuses on the challenges of rural economic development under the strategy of rural revitalization,and deeply analyzes the current situation of rural economic development.Research has found that although the rural revitalization strategy has achieved significant results in improving residents’quality of life,promoting agricultural modernization,it still faces challenges such as severe loss of human resources,insufficient agricultural technological innovation,and backward infrastructure construction.In response to these challenges,this paper proposes optimization strategies from three aspects:strengthening rural education and talent team construction,promoting agricultural technology innovation and achievement transformation,and increasing investment in rural infrastructure construction.
基金supported by the National Natural Science Foundation of China,82471345(to LC)the Key Research and Development Program for Social Development by the Jiangsu Provincial Department of Science and Technology.No.BE2022668(to LC).
文摘Ischemic stroke is a major cause of neurological deficits and high disability rate.As the primary immune cells of the central nervous system,microglia play dual roles in neuroinflammation and tissue repair following a stroke.Their dynamic activation and polarization states are key factors that influence the disease process and treatment outcomes.This review article investigates the role of microglia in ischemic stroke and explores potential intervention strategies.Microglia exhibit a dynamic functional state,transitioning between pro-inflammatory(M1)and anti-inflammatory(M2)phenotypes.This duality is crucial in ischemic stroke,as it maintains a balance between neuroinflammation and tissue repair.Activated microglia contribute to neuroinflammation through cytokine release and disruption of the blood-brain barrier,while simultaneously promoting tissue repair through anti-inflammatory responses and regeneration.Key pathways influencing microglial activation include Toll-like receptor 4/nuclear factor kappa B,mitogen-activated protein kinases,Janus kinase/signal transducer and activator of transcription,and phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin pathways.These pathways are targets for various experimental therapies aimed at promoting M2 polarization and mitigating damage.Potential therapeutic agents include natural compounds found in drugs such as minocycline,as well as traditional Chinese medicines.Drugs that target these regulatory mechanisms,such as small molecule inhibitors and components of traditional Chinese medicines,along with emerging technologies such as single-cell RNA sequencing and spatial transcriptomics,offer new therapeutic strategies and clinical translational potential for ischemic stroke.
基金Supported by Talent Scientific Research Start-up Foundation of Wannan Medical College,No.WYRCQD2023045.
文摘BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To develop an interpretable noninvasive early diagnostic model for PDAC using plasma extracellular vesicle long RNA(EvlRNA).METHODS The diagnostic model was constructed based on plasma EvlRNA data.During the process of establishing the model,EvlRNA-index was introduced,and four algorithms were adopted to calculate EvlRNA-index.After the model was successfully constructed,performance evaluation was conducted.A series of bioinformatics methods were adopted to explore the potential mechanism of EvlRNA-index as the input feature of the model.And the relationship between key characteristics and PDAC were explored at the single-cell level.RESULTS A novel interpretable machine learning framework was developed based on plasma EvlRNA.In this framework,a two-layer classifier was established.A new concept was proposed:EvlRNA-index.Based on EvlRNA-index,a cancer diagnostic model was established,and a good diagnostic effect was achieved.The accuracy of PDACandCPvsHealth-Probabilistic PCA Index-SVM(PDAC and chronic pancreatitis vs health-probabilistic principal component analysis index-support vector machine)(1-18)was 91.51%,with Mathew’s correlation coefficient 0.7760 and area under the curve 0.9560.In the second layer of the model,the accuracy of PDACvsCP-Probabilistic PCA Index-RF(PDAC vs chronic pancreatitis-probabilistic principal component analysis index-random forest)(2-17)was 93.83%,with Mathew’s correlation coefficient 0.8422 and area under the curve 0.9698.Forty-nine PDAC-related genes were identified,among which 16 were known,inferring that the remaining ones were also PDAC-related genes.CONCLUSION An interpretable two-layer machine learning framework was proposed for early diagnosis and prediction of PDAC based on plasma EvlRNA,providing new insights into the clinical value of EvlRNA.
文摘Dove’s 2017 advertising incident,which sparked widespread debate regarding perceived cultural insensitivity,highlighted a disconnect between the brand’s“Real Beauty”positioning and public reception.In response,this study proposes a strategic digital recovery framework,including revised campaign content,transparent communication through social media,and data-driven customer segmentation based on diverse skincare needs and cultural backgrounds.A PESTLE analysis underscores the importance of digital transformation and rising social consciousness in brand management.Findings suggest that inclusive messaging,precision targeting,and omnichannel digital engagement are key to restoring brand trust and reputation in the digital landscape.
文摘In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the operational characteristics of rural microgrids and their impact on users,this paper establishes a two-layer scheduling model incorporating flexible loads.The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid,while the lower-layer aims to minimize the total electricity cost for rural users.An Improved Adaptive Genetic Algorithm(IAGA)is proposed to solve the model.Results show that the two-layer scheduling model with flexible loads can effectively smooth load fluctuations,enhance microgrid stability,increase clean energy consumption,and balance microgrid operating costs with user benefits.
基金the support from Base for Interdisciplinary Innovative Talent Training,Shanghai Jiao Tong UniversityYouth Science and Technology Innovation Studio of Shanghai Jiao Tong University School of Medicine。
文摘Neural injuries can cause considerable functional impairments,and both central and peripheral nervous systems have limited regenerative capacity.The existing conventional pharmacological treatments in clinical practice show poor targeting,rapid drug clearance from the circulatory system,and low therapeutic efficiency.Therefore,in this review,we have first described the mechanisms underlying nerve regeneration,characterized the biomaterials used for drug delivery to facilitate nerve regeneration,and highlighted the functionalization strategies used for such drug-delivery systems.These systems mainly use natural and synthetic polymers,inorganic materials,and hybrid systems with advanced drug-delivery abilities,including nanoparticles,hydrogels,and scaffoldbased systems.Then,we focused on comparing the types of drug-delivery systems for neural regeneration as well as the mechanisms and challenges associated with targeted delivery of drugs to facilitate neural regeneration.Finally,we have summarized the clinical application research and limitations of targeted delivery of these drugs.These biomaterials and drug-delivery systems can provide mechanical support,sustained release of bioactive molecules,and enhanced intercellular contact,ultimately reducing cell apoptosis and enhancing functional recovery.Nevertheless,immune reactions,degradation regulation,and clinical translations remain major unresolved challenges.Future studies should focus on optimizing biomaterial properties,refining delivery precision,and overcoming translational barriers to advance these technologies toward clinical applications.
基金supports from the National Natural Science Foundation of China(Grant Nos.12305372 and 22376217)the National Key Research&Development Program of China(Grant Nos.2022YFA1603802 and 2022YFB3504100)+1 种基金the projects of the key laboratory of advanced energy materials chemistry,ministry of education(Nankai University)key laboratory of Jiangxi Province for persistent pollutants prevention control and resource reuse(2023SSY02061)are gratefully acknowledged.
文摘Using photoelectrocatalytic CO_(2) reduction reaction(CO_(2)RR)to produce valuable fuels is a fascinating way to alleviate environmental issues and energy crises.Bismuth-based(Bi-based)catalysts have attracted widespread attention for CO_(2)RR due to their high catalytic activity,selectivity,excellent stability,and low cost.However,they still need to be further improved to meet the needs of industrial applications.This review article comprehensively summarizes the recent advances in regulation strategies of Bi-based catalysts and can be divided into six categories:(1)defect engineering,(2)atomic doping engineering,(3)organic framework engineering,(4)inorganic heterojunction engineering,(5)crystal face engineering,and(6)alloying and polarization engineering.Meanwhile,the corresponding catalytic mechanisms of each regulation strategy will also be discussed in detail,aiming to enable researchers to understand the structure-property relationship of the improved Bibased catalysts fundamentally.Finally,the challenges and future opportunities of the Bi-based catalysts in the photoelectrocatalytic CO_(2)RR application field will also be featured from the perspectives of the(1)combination or synergy of multiple regulatory strategies,(2)revealing formation mechanism and realizing controllable synthesis,and(3)in situ multiscale investigation of activation pathways and uncovering the catalytic mechanisms.On the one hand,through the comparative analysis and mechanism explanation of the six major regulatory strategies,a multidimensional knowledge framework of the structure-activity relationship of Bi-based catalysts can be constructed for researchers,which not only deepens the atomic-level understanding of catalytic active sites,charge transport paths,and the adsorption behavior of intermediate products,but also provides theoretical guiding principles for the controllable design of new catalysts;on the other hand,the promising collaborative regulation strategies,controllable synthetic paths,and the in situ multiscale characterization techniques presented in this work provides a paradigm reference for shortening the research and development cycle of high-performance catalysts,conducive to facilitating the transition of photoelectrocatalytic CO_(2)RR technology from the laboratory routes to industrial application.
基金sponsored by National Natural Science Foundation of China (Nos. 61673327, 51606161, 11602209, 91441128)Natural Science Foundation of Fujian Province of China (No. 2016J06011)China Scholarship Council (No. 201606310153)
文摘This paper addresses a target-enclosing problem for multiple spacecraft systems by proposing a two-layer affine formation control strategy. Compared with the existing methods,the adopted two-layer network structure in this paper is generally directed, which is suitable for practical space missions. Firstly, distributed finite-time sliding-mode estimators and formation controllers in both layers are designed separately to improve the flexibility of the formation control system. By introducing the properties of affine transformation into formation control protocol design,the controllers can be used to track different time-varying target formation patterns. Besides, multilayer time-varying encirclements can be achieved with particular shapes to surround the moving target. In the sequel, by integrating adaptive neural networks and specialized artificial potential functions into backstepping controllers, the problems of uncertain Euler-Lagrange models, collision avoidance as well as formation reconfiguration are solved simultaneously. The stability of the proposed controllers is verified by the Lyapunov direct method. Finally, two simulation examples of triangle formation and more complex hexagon formation are presented to illustrate the feasibility of the theoretical results.
基金Supported by the National Natural Science Foundation of China(Grant No.40674063)National Hi-tech Research and Development Program of China(863Program)(Grant No.2006AA09Z311)
文摘Based on the synchronous joint gravity and magnetic inversion of single interface by Pilkington and the need of revealing Cenozoic and crystalline basement thickness in the new round of oil-gas exploration, we propose a joint gravity and magnetic inversion methodfor two-layer models by concentrating on the relationship between the change of thicknessI and position of the middle layer and anomaly and discuss the effects of the key parameters. Model tests and application to field data show the validity of this method.
文摘A model is proposed to evaluate the,effective modufi of a composite reinforced by two-layered spherical inclusions.This model is based on the localisation problem of a two- layered spherical inclusion embedded in an infinite matrix.The interations of the reinforced phases are taken into account by using the average matrix stress concept.When the external layer vanishes,the proposed model reduces to the classical Mori-Tanaka's model for spherical inclusions.Theoretical results for the composite of polyester matrix filled by hollow glass spheres and voids show excellent agreement with experimental results.
基金financial support from the Project of National Science Foundation of China(Grant No.41272346)the National Outstanding Youth Funds(Grant No.41225011)+2 种基金financial support from the Science & Technology Research Plan of China Railway Eryuan Engineering Group CO.LTD (Grant No.13164196(13-15))the Project of National Science Foundation of China(Grant Nos. 41472293,91430105)"hundred talents" program of CAS
文摘Many rock avalanches were triggered by the Wenchuan earthquake on May 12, 2008 in southwest China. Protection galleries covered with a single soil layer are usually used to protect against rockfall. Since one-layer protection galleries do not have sufficient buffer capacity, a two-layered absorbing system has been designed. This study aims to find whether an expanded poly-styrol （EPS） cushion, which is used in the soil-covered protection galleries for shock absorption, could be positioned under dynamic loadings. The dynamic impacts of the two-layered absorbing system under the conditions of rock avalanches are numerically simulated through a 2D discrete dement method. By selecting reasonable parameters, a series of numerical experiments were conducted to find the best combination for the two- layered absorbing system. The values of the EPS layer area as a percentage of the total area were set as 0% （Sl）, 22~ （S2）, and 70% （$3）. 22~ of the area of the EPS layer was found to be a reasonable value, and experiments were conducted to find the best position of the EPS layer in the two-layered absorbing system. The numerical results yield useful conclusions regarding the interaction between the impacting avalanches and the two-layered absorbing system. The soil layer can absorb the shock energy effectively and S2 （0.4-m thick EPS cushion covered with soil layer） is the most efficient combination, which can reduce the impact force, compared with the other combinations.
