In recent years,there has been a surge of interest in higher-order topological phases(HOTPs)across various disciplines within the field of physics.These unique phases are characterized by their ability to harbor topol...In recent years,there has been a surge of interest in higher-order topological phases(HOTPs)across various disciplines within the field of physics.These unique phases are characterized by their ability to harbor topological protected boundary states at lower-dimensional boundaries,a distinguishing feature that sets them apart from conventional topological phases and is attributed to the higher-order bulk-boundary correspondence.Two-dimensional(2D)twisted systems offer an optimal platform for investigating HOTPs,owing to their strong controllability and experimental feasibility.Here,we provide a comprehensive overview of the latest research advancements on HOTPs in 2D twisted multilayer systems.We will mainly review the HOTPs in electronic,magnonic,acoustic,photonic and mechanical twisted systems,and finally provide a perspective of this topic.展开更多
Near-field radiative heat transfer(NFRHT) research is an important research project after a major breakthrough in nanotechnology. Based on the multilayer structure, we find that due to the existence of inherent losses...Near-field radiative heat transfer(NFRHT) research is an important research project after a major breakthrough in nanotechnology. Based on the multilayer structure, we find that due to the existence of inherent losses,the decoupling of hyperbolic modes(HMs) after changing the filling ratio leads to suppression of heat flow near the surface mode resonance frequency. It complements the physical landscape of enhancement of near-field radiative heat transfer by HMs and more surface states supported by multiple surfaces. More importantly, considering the difficulty of accurate preparation at the nanoscale, we introduce the disorder factor to describe the magnitude of the random variation of the layer thickness of the multilayer structure and then explore the effect on heat transfer when the layer thickness is slightly different from the exact value expected. We find that the near-field radiative heat flux decreases gradually as the disorder increases because of interlayer energy localization. However, the reduction in heat transfer does not exceed an order of magnitude, although the disorder is already very large. At the same time, the regulation effect of the disorder on NFRHT is close to that of the same degree of filling ratio,which highlights the importance of disordered systems. This work qualitatively describes the effect of disorder on heat transfer and provides instructive data for the fabrication of NFRHT devices.展开更多
The healthcare data requires accurate disease detection analysis,real-timemonitoring,and advancements to ensure proper treatment for patients.Consequently,Machine Learning methods are widely utilized in Smart Healthca...The healthcare data requires accurate disease detection analysis,real-timemonitoring,and advancements to ensure proper treatment for patients.Consequently,Machine Learning methods are widely utilized in Smart Healthcare Systems(SHS)to extract valuable features fromheterogeneous and high-dimensional healthcare data for predicting various diseases and monitoring patient activities.These methods are employed across different domains that are susceptible to adversarial attacks,necessitating careful consideration.Hence,this paper proposes a crossover-based Multilayer Perceptron(CMLP)model.The collected samples are pre-processed and fed into the crossover-based multilayer perceptron neural network to detect adversarial attacks on themedical records of patients.Once an attack is detected,healthcare professionals are promptly alerted to prevent data leakage.The paper utilizes two datasets,namely the synthetic dataset and the University of Queensland Vital Signs(UQVS)dataset,from which numerous samples are collected.Experimental results are conducted to evaluate the performance of the proposed CMLP model,utilizing various performancemeasures such as Recall,Precision,Accuracy,and F1-score to predict patient activities.Comparing the proposed method with existing approaches,it achieves the highest accuracy,precision,recall,and F1-score.Specifically,the proposedmethod achieves a precision of 93%,an accuracy of 97%,an F1-score of 92%,and a recall of 92%.展开更多
Lightweight,high-strength,and heat-resistant protective structures have consistently been crucial for applications in extreme environments,such as aerospace,semiconductors,and nuclear power industries.Multilayered TC4...Lightweight,high-strength,and heat-resistant protective structures have consistently been crucial for applications in extreme environments,such as aerospace,semiconductors,and nuclear power industries.Multilayered TC4/TB8 titanium(Ti)laminates,inspired by theheterostructures of natural biological shells,were fabricated using a hybrid diffusion bonding-hot rolling process followed by an aging treatment,resulting in an architected micro structure.The laminate achieves an ultra-high yield stress of 1020 MPa and proper uniform elongation of 4.2%at 500℃.The TB8 layers with high-density nano-precipitates and dislocations act as hard zone,contributing to high strength.The TC4 layers,with their bimodal structure consisting of coarse and fine grains characterized by equiaxed and lamellar structures,experience more plastic strain than the TB8 layers.The hetero deformation associated with the detwinning ofαgrains in the TC4 layer induces toughening at high temperatures.展开更多
To overcome the shortage of complex equipment,large volume,and high energy consumption in space capsule manufacturing,a novel sliding pressure Joule heat fuse additive manufacturing technique with reduced volume and l...To overcome the shortage of complex equipment,large volume,and high energy consumption in space capsule manufacturing,a novel sliding pressure Joule heat fuse additive manufacturing technique with reduced volume and low energy consumption was proposed.But the unreasonable process parameters may lead to the inferior consistency of the forming quality of single-channel multilayer in Joule heat additive manufacturing process,and it is difficult to reach the condition for forming thinwalled parts.Orthogonal experiments were designed to fabricate single-channel multilayer samples with varying numbers of layers,and their forming quality was evaluated.The influence of printing current,forming speed,and contact pressure on the forming quality of the single-channel multilayer was analyzed.The optimal process parameters were obtained and the quality characterization of the experiment results was conducted.Results show that the printing current has the most significant influence on the forming quality of the single-channel multilayer.Under the optimal process parameters,the forming section is well fused and the surface is continuously smooth.The surface roughness of a single-channel 3-layer sample is 0.16μm,and the average Vickers hardness of cross section fusion zone is 317 HV,which lays a foundation for the subsequent use of Joule heat additive manufacturing technique to form thinwall parts.展开更多
In this paper,we theoretically study the Lamb wave in a multilayered piezoelectric semiconductor(PSC)plate,where each layer is an n-type PSC with the symmetry of transverse isotropy.Based on the extended Stroh formali...In this paper,we theoretically study the Lamb wave in a multilayered piezoelectric semiconductor(PSC)plate,where each layer is an n-type PSC with the symmetry of transverse isotropy.Based on the extended Stroh formalism and dual-variable and position(DVP)method,the general solution of the coupled fields for the Lamb wave is derived,and then the dispersion equation is obtained by the application of the boundary conditions.First,the influence of semiconducting properties on the dispersion behavior of the Lamb wave in a single-layer PSC plate is analyzed.Then,the propagation characteristics of the Lamb wave in a sandwich plate are investigated in detail.The numerical results show that the wave speed and attenuation depend on the stacking sequence,layer thickness,and initial carrier density,the Lamb wave can propagate without a cut-off frequency in both the homogeneous and multilayer PSC plates due to the semiconducting properties,and the Lamb wave without attenuation can be achieved by carefully selecting the semiconductor property in the upper and lower layers.These new features could be very helpful as theoretical guidance for the design and performance optimization of PSC devices.展开更多
Perovskite solar cells(PSCs)have been receiving attention for photovoltaic advantages of high-power conversion efficiency,cost-effectiveness,and easy fabrication process.Particularly,flexible PSCs(FPSCs)are considered...Perovskite solar cells(PSCs)have been receiving attention for photovoltaic advantages of high-power conversion efficiency,cost-effectiveness,and easy fabrication process.Particularly,flexible PSCs(FPSCs)are considered to be promising renewable power sources due to the positive potential of flexible and lightweight properties.However,FPSCs tend to have lower efficiency compared to glass-based rigid PSCs(RPSCs).The main issue is high refractive index of polymer substrates such as polyethylene naphthalate(PEN),used for FPSCs,thereby reducing the external light absorption efficiency.In this study,we developed glasswing inspired sticker-type multilayer anti-reflective(GSMA)film derived from the wings of the glasswing butterfly to enhance the light absorption efficiency of FPSCs.We designed and fabricated the GSMA film with multilayers specifically for FPSCs.The suitable materials and nanostructures to adjust the refractive index are theoretically optimized.The GSMA film effectively improved the optical properties of PSC substrates,reducing reflectance(∼5.01%)and enhancing light transmittance(∼6.17%)in indium tin oxide(ITO)/PEN.In addition,the GSMA film on PEN maintains more than 94.70%of its initial transmittance even after being exposed to various harsh environments for 500 h,and GSMA film demonstrates flexibility by maintaining its initial structure even after a bending test(bending radius of 1 mm).The FPSCs and RPSCs assisted by GSMA film show high short-circuit current density(FPSC:∼25.28 mA/cm^(2),up to 26.05 mA/cm^(2),RPSC:∼24.27 mA/cm^(2))and power conversion efficiency(FPSC:∼22.72%,RPSC:∼22.31%),significantly narrowing the efficiency gap between FPSC and RPSCs.展开更多
Intrusion detection systems play a vital role in cyberspace security.In this study,a network intrusion detection method based on the feature selection algorithm(FSA)and a deep learning model is developed using a fusio...Intrusion detection systems play a vital role in cyberspace security.In this study,a network intrusion detection method based on the feature selection algorithm(FSA)and a deep learning model is developed using a fusion of a recursive feature elimination(RFE)algorithm and a bidirectional gated recurrent unit(BGRU).Particularly,the RFE algorithm is employed to select features from high-dimensional data to reduce weak correlations between features and remove redundant features in the numerical feature space.Then,a neural network that combines the BGRU and multilayer perceptron(MLP)is adopted to extract deep intrusion behavior features.Finally,a support vector machine(SVM)classifier is used to classify intrusion behaviors.The proposed model is verified by experiments on the NSL-KDD dataset.The results indicate that the proposed model achieves a 90.25%accuracy and a 97.51%detection rate in binary classification and outperforms other machine learning and deep learning models in intrusion classification.The proposed method can provide new insight into network intrusion detection.展开更多
Electron doping has been established as an effective method to enhance the superconducting transition temperature and superconducting energy gap of FeSe thin films on strontium titanate(SrTiO_(3))substrates.Previous s...Electron doping has been established as an effective method to enhance the superconducting transition temperature and superconducting energy gap of FeSe thin films on strontium titanate(SrTiO_(3))substrates.Previous studies have demonstrated that electron/hole doping can be achieved through the adsorption of metal phthalocyanine(MPc,M=Co,Cu,Mn,Fe,and Ni)molecules on surfaces.This work explores the electron doping induced by the adsorption of MPc molecules,specifically cobalt phthalocyanine(CoPc)and copper phthalocyanine(CuPc),onto FeSe monolayer and multilayers.Utilizing first-principles calculations based on density functional theory,we demonstrate that charge rearrangement occurs when MPc molecules adsorb on the FeSe substrate,contributing to an accumulation of electrons at the interface.In the CoPc/FeSe systems,the electron accumulation increases with the layer number of FeSe substrate,converging for substrates with 3-5 layers.The analysis of the integrated planar charge difference up to the position with zero integrated charge transfer reveals that all the five MPc molecules donate electrons to the uppermost FeSe layer.The electron donation suggests that MPc adsorption can be a promising strategy to modulate the superconductivity of FeSe layers.展开更多
In the multilayer film-substrate system,thermal stress concentration and stress mutations cause film buckling,delamination and cracking,leading to device failure.In this paper,we investigated a multilayer film system ...In the multilayer film-substrate system,thermal stress concentration and stress mutations cause film buckling,delamination and cracking,leading to device failure.In this paper,we investigated a multilayer film system composed of a substrate and three film layers.The thermal stress distribution inside the structure was calculated by the finite element method,revealing significant thermal stress differences between the layers.This is mainly due to the mismatch of the coefficient of thermal expansion between materials.Different materials respond differently to changes in external temperature,leading to compression between layers.There are obvious thermal stress concentration points at the corners of the base layer and the transition layer,which is due to the sudden change of the shape at the geometric section of the structure,resulting in a sudden increase in local stress.To address this issue,we chamfered the substrate and added an intermediate layer between the substrate and the transition layer to assess whether these modifications could reduce or eliminate the thermal stress concentration points and extend the service life of the multilayer structure.The results indicate that chamfering and adding the intermediate layer effectively reduce stress discontinuities and mitigate thermal stress concentration points,thereby improving interlayer bonding strength.展开更多
In rotationally extruded fittings,high-density polyethylene(HDPE)pipes prepared using conventional processing methods often suffer from poor pressure resistance and low toughness.This study introduces an innovative ro...In rotationally extruded fittings,high-density polyethylene(HDPE)pipes prepared using conventional processing methods often suffer from poor pressure resistance and low toughness.This study introduces an innovative rotary shear system(RSS)to address these deficiencies through controlled mandrel rotation and cooling rates.We successfully prepared self-reinforced HDPE pipes with a three-layer structure combining spherical and shish-kebab crystals.Rotational processing aligned the molecular chains in the ring direction and formed shish-kebab crystals.As a result,the annular tensile strength of the rotationally processed three-layer shish-kebab structure(TSK)pipe increased from 26.7 MPa to 76.3 MPa,an enhancement of 185.8%.Notably,while maintaining excellent tensile strength(73.4 MPa),the elongation at break of the spherulite shishkebab spherulite(SKS)tubes was improved to 50.1%,as compared to 33.8%in the case of shish-kebab spherulite shish-kebab(KSK)tubes.This improvement can be attributed to the changes in the micro-morphology and polymer structure within the SKS tubes,specifically due to the formation of small-sized shish-kebab crystals and the low degrees of interlocking.In addition,2D-SAXS analysis revealed that KSK tubes have higher tensile strength due to smaller crystal sizes and larger shish dimensions,forming dense interlocking structures.In contrast,the SKS and TSK tubes had thicker amorphous regions and smaller shish sizes,resulting in reduced interlocking and mechanical performance.展开更多
Research on the self-similarity of multilayer networks is scarce, when compared to the extensive research conducted on the dynamics of these networks. In this paper, we use entropy to determine the edge weights in eac...Research on the self-similarity of multilayer networks is scarce, when compared to the extensive research conducted on the dynamics of these networks. In this paper, we use entropy to determine the edge weights in each sub-network,and apply the degree–degree distance to unify the weight values of connecting edges between different sub-networks, and unify the edges with different meanings in the multilayer network numerically. At this time, the multilayer network is compressed into a single-layer network, also known as the aggregated network. Furthermore, the self-similarity of the multilayer network is represented by analyzing the self-similarity of the aggregate network. The study of self-similarity was conducted on two classical fractal networks and a real-world multilayer network. The results show that multilayer networks exhibit more pronounced self-similarity, and the intensity of self-similarity in multilayer networks can vary with the connection mode of sub-networks.展开更多
The Multilayer Perceptron(MLP)is a fundamental neural network model widely applied in various domains,particularly for lightweight image classification,speech recognition,and natural language processing tasks.Despite ...The Multilayer Perceptron(MLP)is a fundamental neural network model widely applied in various domains,particularly for lightweight image classification,speech recognition,and natural language processing tasks.Despite its widespread success,training MLPs often encounter significant challenges,including susceptibility to local optima,slow convergence rates,and high sensitivity to initial weight configurations.To address these issues,this paper proposes a Latin Hypercube Opposition-based Elite Variation Artificial Protozoa Optimizer(LOEV-APO),which enhances both global exploration and local exploitation simultaneously.LOEV-APO introduces a hybrid initialization strategy that combines Latin Hypercube Sampling(LHS)with Opposition-Based Learning(OBL),thus improving the diversity and coverage of the initial population.Moreover,an Elite Protozoa Variation Strategy(EPVS)is incorporated,which applies differential mutation operations to elite candidates,accelerating convergence and strengthening local search capabilities around high-quality solutions.Extensive experiments are conducted on six classification tasks and four function approximation tasks,covering a wide range of problem complexities and demonstrating superior generalization performance.The results demonstrate that LOEV-APO consistently outperforms nine state-of-the-art metaheuristic algorithms and two gradient-based methods in terms of convergence speed,solution accuracy,and robustness.These findings suggest that LOEV-APO serves as a promising optimization tool for MLP training and provides a viable alternative to traditional gradient-based methods.展开更多
Design of a miniaturized lumped-element bandpass filter in multilayer liquid crystal polymer technology is proposed.Fractional bandwidth of the bandpass filter is 20%,operating at a center frequency of 500 MHz.In orde...Design of a miniaturized lumped-element bandpass filter in multilayer liquid crystal polymer technology is proposed.Fractional bandwidth of the bandpass filter is 20%,operating at a center frequency of 500 MHz.In order to further reduce the size and improve the performance of the proposed filter,defected ground structure(DGS)has been implemented in the filter.Based on this structure,the volume of the inductor is reduced by 60%eficiently compared with the inductor without DGS,and the Q-factor is increased up to 257%compared with the traditional multilayer spiral inductor.The measured results indicate that the designed filter has a very sharp stopband,an insertion loss of 2.3dB,and a return loss of 18.6dB in the passband.The whole volume of the fabricated filter is 0.032入_(g)×0.05入_(g)×0.00075入_(g),where Ag is the guided wavelength of the center frequency.The proposed filter is easily integrated into radio-frequency/microwave circuitry at a low manufacturing cost,especially wireless communication.展开更多
This study presents a wireless photovoltaic fault monitoring system integrating an STM32 microcontroller with an Improved Horned Lizard Optimization Algorithm(IHLOA)and a Multi-Layer Perceptron(MLP)neural network.The ...This study presents a wireless photovoltaic fault monitoring system integrating an STM32 microcontroller with an Improved Horned Lizard Optimization Algorithm(IHLOA)and a Multi-Layer Perceptron(MLP)neural network.The IHLOA algorithm introduces three key innovations:(1)chaotic initialization to enhance population diversity and global search capability,(2)adaptive random walk strategies to escape local optima,and(3)a cross-strategy mechanism to accelerate convergence and enhance fault detection accuracy and robustness.The system comprises both hardware and software components.The hardware includes sensors such as the BH1750 light intensity sensor,DS18B20 temperature sensor,and INA226 current and voltage sensor,all interfaced with the STM32F103C8T6 microcontroller and the ESP8266 module for wireless data transmission.The software,developed using QT Creator,incorporates an IHLOA-MLP model for fault diagnosis.The user-friendly interface facilitates intuitive monitoring and scalability for multiple systems.Experimental validation on a PV array demonstrates that the IHLOA-MLP model achieves a fault detection accuracy of 94.55%,which is 2.4%higher than the standard MLP,while reducing variance by 63.64%compared to the standard MLP.This highlights its accuracy and robustness.When compared to other optimization algorithms such as BKA-MLP(94.10%accuracy)and HLOA-MLP(94.00%accuracy),the IHLOA-MLP further reduces variance to 0.08,showcasing its superior performance.The system selects voltage as a feature vector to maintain circuit stability,avoiding efficiency impacts from series current sensors.This combined hardware and software approach further reduces false alarms to 0.1%through a consecutive-judgment mechanism,significantly enhancing practical reliability.This work provides a cost-effective and scalable solution for improving the stability and safety of PV systems in real-world applications.展开更多
Thermal conductivity is an important physical parameter in thermal equipment,in the blast furnace,rotary kiln and other equipment,multi-layer cylindrical wall is extremely important in industrial production of a therm...Thermal conductivity is an important physical parameter in thermal equipment,in the blast furnace,rotary kiln and other equipment,multi-layer cylindrical wall is extremely important in industrial production of a thermal conductivity model,its thermal conductivity coefficient determines the ability of the cylindrical wall,which results in the existence of a large number of multi-layer cylinder thermal conductivity problems of the pitfalls.This paper focuses on the establishment of a mathematical model of the multi-layer cylinder thermal conductivity problem,by applying different voltages to the multi-layer cylinder wall,study the temperature distribution of the multi-layer cylinder wall under the conditions of natural convection and forced convection,and draw the line graphs under the conditions of natural convection and forced convection by Origin software,and finally conclude that:under the same conditions,the forced convection is significantly stronger than the natural convection;under the conditions of different voltages,the multi-layer cylinder wall under the conditions of steady state convection,the forced convection is much stronger than natural convection.Under different voltage conditions,the temperature of the multilayer cylinder wall under steady state conditions increases with the increase of voltage,which provides a strong support for the related research.展开更多
Objective:Prostate cancer(PCa)exhibits significant genomic differences between Western and Asian populations.This study aimed to design a predictive model applicable across diverse populations while selecting a limite...Objective:Prostate cancer(PCa)exhibits significant genomic differences between Western and Asian populations.This study aimed to design a predictive model applicable across diverse populations while selecting a limited set of genes suitable for clinical implementation.Methods:We utilized an integrated dataset of 1360 whole-exome and whole-genome sequences from Chinese and Western PCa cohorts to develop and evaluate the model.External validation was conducted using an independent cohort of patients.A graph neural network architecture,termed the pathway-aware multi-layered hierarchical network-Western and Asian(P-NETwa),was developed and trained on combined genomic profiles from Chinese and Western cohorts.The model employed a multilayer perceptron(MLP)to identify key signature genes from multiomics data,enabling precise prediction of PCa metastasis.Results:The model achieved an accuracy of 0.87 and an F1-score of 0.85 on Western population datasets.The application of integrated Chinese and Western population data improved the accuracy to 0.88,achieving an F1-score of 0.75.The analysis identified 18 signature genes implicated in PCa progression,including established markers(AR and TP53)and novel candidates(MUC16,MUC4,and ASB12).For clinical adoption,the model was optimized for commercially available gene panels while maintaining high classification accuracy.Additionally,a user-friendly web interface was developed to facilitate real-time prediction of primary versus metastatic status using the pre-trained P-NETwa-MLP model.Conclusion:The P-NETwa-MLP model integrates a query system that allows for efficient retrieval of prediction outcomes and associated genomic signatures via sample ID,enhancing its potential for seamless integration into clinical workflows.展开更多
The outbreak of COVID-19 in 2019 has made people pay more attention to infectious diseases.In order to reduce the risk of infection and prevent the spread of infectious diseases,it is crucial to strengthen individual ...The outbreak of COVID-19 in 2019 has made people pay more attention to infectious diseases.In order to reduce the risk of infection and prevent the spread of infectious diseases,it is crucial to strengthen individual immunization measures and to restrain the diffusion of negative information relevant to vaccines at the opportune moment.This study develops a three-layer coupling model within the framework of hypernetwork evolution,examining the interplay among negative information,immune behavior,and epidemic propagation.Firstly,the dynamic topology evolution process of hypernetwork includes node joining,aging out,hyperedge adding and reconnecting.The three-layer communication model accounts for the multifaceted influences exerted by official media channels,subjective psychological acceptance capabilities,self-identification abilities,and physical fitness levels.Each level of the decision-making process is described using the Heaviside step function.Secondly,the dynamics equations of each state and the prevalence threshold are derived using the microscopic Markov chain approach(MMCA).The results show that the epidemic threshold is affected by three transmission processes.Finally,through the simulation testing,it is possible to enhance the intensity of official clarification,improve individual self-identification ability and physical fitness,and thereby promote the overall physical enhancement of society.This,in turn,is beneficial in controlling false information,heightening vaccination coverage,and controlling the epidemic.展开更多
Wind power forecasting plays a crucial role in optimizing the integration of wind energy into the grid by predicting wind patterns and energy output.This enhances the efficiency and reliability of renewable energy sys...Wind power forecasting plays a crucial role in optimizing the integration of wind energy into the grid by predicting wind patterns and energy output.This enhances the efficiency and reliability of renewable energy systems.Forecasting approaches inform energy management strategies,reduce reliance on fossil fuels,and support the broader transition to sustainable energy solutions.The primary goal of this study is to introduce an effective methodology for estimating wind power through temporal data analysis.This research advances an optimized Multilayer Perceptron(MLP)model using recently proposedmetaheuristic optimization algorithms,namely the FireHawk Optimizer(FHO)and the Non-Monopolize Search(NO).A modified version of FHO,termed FHONO,is developed by integrating NO as a local search mechanism to enhance the exploration capability and address the shortcomings of the original FHO.The developed FHONO is then employed to optimize the MLP for enhanced wind power prediction.The effectiveness of the proposed FHONO-MLP model is validated using renowned datasets from wind turbines in France.The results of the comparative analysis between FHONO-MLP,conventionalMLP,and other optimized versions of MLP show that FHONO-MLP outperforms the others,achieving an average RootMean Square Error(RMSE)of 0.105,Mean Absolute Error(MAE)of 0.082,and Coefficient of Determination(R^(2))of 0.967 across all datasets.These findings underscore the significant enhancement in predictive accuracy provided by FHONO and demonstrate its effectiveness in improving wind power forecasting.展开更多
As the economy grows, environmental issues are becoming increasingly severe, making the promotion of green behavior more urgent. Information dissemination and policy regulation play crucial roles in influencing and am...As the economy grows, environmental issues are becoming increasingly severe, making the promotion of green behavior more urgent. Information dissemination and policy regulation play crucial roles in influencing and amplifying the spread of green behavior across society. To this end, a novel three-layer model in multilayer networks is proposed. In the novel model, the information layer describes green information spreading, the physical contact layer depicts green behavior propagation, and policy regulation is symbolized by an isolated node beneath the two layers. Then, we deduce the green behavior threshold for the three-layer model using the microscopic Markov chain approach. Moreover, subject to some individuals who are more likely to influence others or become green nodes and the limitations of the capacity of policy regulation, an optimal scheme is given that could optimize policy interventions to most effectively prompt green behavior.Subsequently, simulations are performed to validate the preciseness and theoretical results of the new model. It reveals that policy regulation can prompt the prevalence and outbreak of green behavior. Then, the green behavior is more likely to spread and be prevalent in the SF network than in the ER network. Additionally, optimal allocation is highly successful in facilitating the dissemination of green behavior. In practice, the optimal allocation strategy could prioritize interventions at critical nodes or regions, such as highly connected urban areas, where the impact of green behavior promotion would be most significant.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12304539,12074108,12474151,12347101)the Natural Science Foundation of Chongqing(Grant No.CSTB2022NSCQ-MSX0568)Beijing National Laboratory for Condensed Matter Physics(Grant No.2024BNLCMPKF025)。
文摘In recent years,there has been a surge of interest in higher-order topological phases(HOTPs)across various disciplines within the field of physics.These unique phases are characterized by their ability to harbor topological protected boundary states at lower-dimensional boundaries,a distinguishing feature that sets them apart from conventional topological phases and is attributed to the higher-order bulk-boundary correspondence.Two-dimensional(2D)twisted systems offer an optimal platform for investigating HOTPs,owing to their strong controllability and experimental feasibility.Here,we provide a comprehensive overview of the latest research advancements on HOTPs in 2D twisted multilayer systems.We will mainly review the HOTPs in electronic,magnonic,acoustic,photonic and mechanical twisted systems,and finally provide a perspective of this topic.
基金the National Natural Science Foundation of China(Grant Nos.11974010 and 12274313)the National Key R&D Program of China(Grant Nos.2022YFA1404400 and 2022YFA1404300)。
文摘Near-field radiative heat transfer(NFRHT) research is an important research project after a major breakthrough in nanotechnology. Based on the multilayer structure, we find that due to the existence of inherent losses,the decoupling of hyperbolic modes(HMs) after changing the filling ratio leads to suppression of heat flow near the surface mode resonance frequency. It complements the physical landscape of enhancement of near-field radiative heat transfer by HMs and more surface states supported by multiple surfaces. More importantly, considering the difficulty of accurate preparation at the nanoscale, we introduce the disorder factor to describe the magnitude of the random variation of the layer thickness of the multilayer structure and then explore the effect on heat transfer when the layer thickness is slightly different from the exact value expected. We find that the near-field radiative heat flux decreases gradually as the disorder increases because of interlayer energy localization. However, the reduction in heat transfer does not exceed an order of magnitude, although the disorder is already very large. At the same time, the regulation effect of the disorder on NFRHT is close to that of the same degree of filling ratio,which highlights the importance of disordered systems. This work qualitatively describes the effect of disorder on heat transfer and provides instructive data for the fabrication of NFRHT devices.
基金funded by King Saud University through Researchers Supporting Program Number (RSP2024R499).
文摘The healthcare data requires accurate disease detection analysis,real-timemonitoring,and advancements to ensure proper treatment for patients.Consequently,Machine Learning methods are widely utilized in Smart Healthcare Systems(SHS)to extract valuable features fromheterogeneous and high-dimensional healthcare data for predicting various diseases and monitoring patient activities.These methods are employed across different domains that are susceptible to adversarial attacks,necessitating careful consideration.Hence,this paper proposes a crossover-based Multilayer Perceptron(CMLP)model.The collected samples are pre-processed and fed into the crossover-based multilayer perceptron neural network to detect adversarial attacks on themedical records of patients.Once an attack is detected,healthcare professionals are promptly alerted to prevent data leakage.The paper utilizes two datasets,namely the synthetic dataset and the University of Queensland Vital Signs(UQVS)dataset,from which numerous samples are collected.Experimental results are conducted to evaluate the performance of the proposed CMLP model,utilizing various performancemeasures such as Recall,Precision,Accuracy,and F1-score to predict patient activities.Comparing the proposed method with existing approaches,it achieves the highest accuracy,precision,recall,and F1-score.Specifically,the proposedmethod achieves a precision of 93%,an accuracy of 97%,an F1-score of 92%,and a recall of 92%.
基金financially supported by the Natural Science Foundation of Changsha,China(No.kq2402015)the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIP)(Nos.NRF-2021R1A2C3006662 and NRF-2022R1A5A1030054)supported by Brain Pool Program through the NRF of Korea,funded by the Ministry of Science and ICT(No.NRF-RS_(2)02300263999)
文摘Lightweight,high-strength,and heat-resistant protective structures have consistently been crucial for applications in extreme environments,such as aerospace,semiconductors,and nuclear power industries.Multilayered TC4/TB8 titanium(Ti)laminates,inspired by theheterostructures of natural biological shells,were fabricated using a hybrid diffusion bonding-hot rolling process followed by an aging treatment,resulting in an architected micro structure.The laminate achieves an ultra-high yield stress of 1020 MPa and proper uniform elongation of 4.2%at 500℃.The TB8 layers with high-density nano-precipitates and dislocations act as hard zone,contributing to high strength.The TC4 layers,with their bimodal structure consisting of coarse and fine grains characterized by equiaxed and lamellar structures,experience more plastic strain than the TB8 layers.The hetero deformation associated with the detwinning ofαgrains in the TC4 layer induces toughening at high temperatures.
基金Shaanxi Province Qin Chuangyuan“Scientist+Engineer”Team Construction Project(2022KXJ-071)2022 Qin Chuangyuan Achievement Transformation Incubation Capacity Improvement Project(2022JH-ZHFHTS-0012)+1 种基金Shaanxi Province Key Research and Development Plan-“Two Chains”Integration Key Project-Qin Chuangyuan General Window Industrial Cluster Project(2023QCY-LL-02)Xixian New Area Science and Technology Plan(2022-YXYJ-003,2022-XXCY-010)。
文摘To overcome the shortage of complex equipment,large volume,and high energy consumption in space capsule manufacturing,a novel sliding pressure Joule heat fuse additive manufacturing technique with reduced volume and low energy consumption was proposed.But the unreasonable process parameters may lead to the inferior consistency of the forming quality of single-channel multilayer in Joule heat additive manufacturing process,and it is difficult to reach the condition for forming thinwalled parts.Orthogonal experiments were designed to fabricate single-channel multilayer samples with varying numbers of layers,and their forming quality was evaluated.The influence of printing current,forming speed,and contact pressure on the forming quality of the single-channel multilayer was analyzed.The optimal process parameters were obtained and the quality characterization of the experiment results was conducted.Results show that the printing current has the most significant influence on the forming quality of the single-channel multilayer.Under the optimal process parameters,the forming section is well fused and the surface is continuously smooth.The surface roughness of a single-channel 3-layer sample is 0.16μm,and the average Vickers hardness of cross section fusion zone is 317 HV,which lays a foundation for the subsequent use of Joule heat additive manufacturing technique to form thinwall parts.
基金Project supported by the National Natural Science Foundation of China(Nos.U21A20430 and 12302202)the Hebei Natural Science Foundation of China(No.A2023210040)+1 种基金the Science and Technology Project of Hebei Education Department of China(No.BJ2025005)the Hebei Provincial Department of Human Resources and Social Security of China(No.C20220324)。
文摘In this paper,we theoretically study the Lamb wave in a multilayered piezoelectric semiconductor(PSC)plate,where each layer is an n-type PSC with the symmetry of transverse isotropy.Based on the extended Stroh formalism and dual-variable and position(DVP)method,the general solution of the coupled fields for the Lamb wave is derived,and then the dispersion equation is obtained by the application of the boundary conditions.First,the influence of semiconducting properties on the dispersion behavior of the Lamb wave in a single-layer PSC plate is analyzed.Then,the propagation characteristics of the Lamb wave in a sandwich plate are investigated in detail.The numerical results show that the wave speed and attenuation depend on the stacking sequence,layer thickness,and initial carrier density,the Lamb wave can propagate without a cut-off frequency in both the homogeneous and multilayer PSC plates due to the semiconducting properties,and the Lamb wave without attenuation can be achieved by carefully selecting the semiconductor property in the upper and lower layers.These new features could be very helpful as theoretical guidance for the design and performance optimization of PSC devices.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2020R1I1A3054824)supported by the Nano&Material Technology Development Program(RS-2023-00282896)through the National Research Foundation of Korea(NRF)funded by Ministry of Science and ICT。
文摘Perovskite solar cells(PSCs)have been receiving attention for photovoltaic advantages of high-power conversion efficiency,cost-effectiveness,and easy fabrication process.Particularly,flexible PSCs(FPSCs)are considered to be promising renewable power sources due to the positive potential of flexible and lightweight properties.However,FPSCs tend to have lower efficiency compared to glass-based rigid PSCs(RPSCs).The main issue is high refractive index of polymer substrates such as polyethylene naphthalate(PEN),used for FPSCs,thereby reducing the external light absorption efficiency.In this study,we developed glasswing inspired sticker-type multilayer anti-reflective(GSMA)film derived from the wings of the glasswing butterfly to enhance the light absorption efficiency of FPSCs.We designed and fabricated the GSMA film with multilayers specifically for FPSCs.The suitable materials and nanostructures to adjust the refractive index are theoretically optimized.The GSMA film effectively improved the optical properties of PSC substrates,reducing reflectance(∼5.01%)and enhancing light transmittance(∼6.17%)in indium tin oxide(ITO)/PEN.In addition,the GSMA film on PEN maintains more than 94.70%of its initial transmittance even after being exposed to various harsh environments for 500 h,and GSMA film demonstrates flexibility by maintaining its initial structure even after a bending test(bending radius of 1 mm).The FPSCs and RPSCs assisted by GSMA film show high short-circuit current density(FPSC:∼25.28 mA/cm^(2),up to 26.05 mA/cm^(2),RPSC:∼24.27 mA/cm^(2))and power conversion efficiency(FPSC:∼22.72%,RPSC:∼22.31%),significantly narrowing the efficiency gap between FPSC and RPSCs.
基金supported in part by the National Natural Science Foundation of China(No.62001333)the Scientific Research Project of Education Department of Hubei Province(No.D20221702).
文摘Intrusion detection systems play a vital role in cyberspace security.In this study,a network intrusion detection method based on the feature selection algorithm(FSA)and a deep learning model is developed using a fusion of a recursive feature elimination(RFE)algorithm and a bidirectional gated recurrent unit(BGRU).Particularly,the RFE algorithm is employed to select features from high-dimensional data to reduce weak correlations between features and remove redundant features in the numerical feature space.Then,a neural network that combines the BGRU and multilayer perceptron(MLP)is adopted to extract deep intrusion behavior features.Finally,a support vector machine(SVM)classifier is used to classify intrusion behaviors.The proposed model is verified by experiments on the NSL-KDD dataset.The results indicate that the proposed model achieves a 90.25%accuracy and a 97.51%detection rate in binary classification and outperforms other machine learning and deep learning models in intrusion classification.The proposed method can provide new insight into network intrusion detection.
基金support from the National Natural Science Foundation of China(Grant No.62488201)the National Key Research and Development Program of China(Grant No.2022YFA1204100).
文摘Electron doping has been established as an effective method to enhance the superconducting transition temperature and superconducting energy gap of FeSe thin films on strontium titanate(SrTiO_(3))substrates.Previous studies have demonstrated that electron/hole doping can be achieved through the adsorption of metal phthalocyanine(MPc,M=Co,Cu,Mn,Fe,and Ni)molecules on surfaces.This work explores the electron doping induced by the adsorption of MPc molecules,specifically cobalt phthalocyanine(CoPc)and copper phthalocyanine(CuPc),onto FeSe monolayer and multilayers.Utilizing first-principles calculations based on density functional theory,we demonstrate that charge rearrangement occurs when MPc molecules adsorb on the FeSe substrate,contributing to an accumulation of electrons at the interface.In the CoPc/FeSe systems,the electron accumulation increases with the layer number of FeSe substrate,converging for substrates with 3-5 layers.The analysis of the integrated planar charge difference up to the position with zero integrated charge transfer reveals that all the five MPc molecules donate electrons to the uppermost FeSe layer.The electron donation suggests that MPc adsorption can be a promising strategy to modulate the superconductivity of FeSe layers.
基金the support of the National Natural Science Foundation of China(Grant Nos.51606158,11604311 and 12074151)the Guangxi Science and Technology Base and Talent Special Project(Grant No.AD21075009)+2 种基金the Sichuan Science and Technology Program(Grant No.2021JDRC0022)the Open Fund of the Key Laboratory for Metallurgical Equipment and Control Technology of Ministry of Education in Wuhan University of Science and Technology,People's Republic of China(Grant Nos.MECOF2022B01 and MECOF2023B04)the Guangxi Key Laboratory of Precision Navigation Technology and Application,Guilin University of Electronic Technology(Grant No.DH202321)。
文摘In the multilayer film-substrate system,thermal stress concentration and stress mutations cause film buckling,delamination and cracking,leading to device failure.In this paper,we investigated a multilayer film system composed of a substrate and three film layers.The thermal stress distribution inside the structure was calculated by the finite element method,revealing significant thermal stress differences between the layers.This is mainly due to the mismatch of the coefficient of thermal expansion between materials.Different materials respond differently to changes in external temperature,leading to compression between layers.There are obvious thermal stress concentration points at the corners of the base layer and the transition layer,which is due to the sudden change of the shape at the geometric section of the structure,resulting in a sudden increase in local stress.To address this issue,we chamfered the substrate and added an intermediate layer between the substrate and the transition layer to assess whether these modifications could reduce or eliminate the thermal stress concentration points and extend the service life of the multilayer structure.The results indicate that chamfering and adding the intermediate layer effectively reduce stress discontinuities and mitigate thermal stress concentration points,thereby improving interlayer bonding strength.
基金supported by the National Natural Science Foundation of China(Nos.52373045 and 52033005).
文摘In rotationally extruded fittings,high-density polyethylene(HDPE)pipes prepared using conventional processing methods often suffer from poor pressure resistance and low toughness.This study introduces an innovative rotary shear system(RSS)to address these deficiencies through controlled mandrel rotation and cooling rates.We successfully prepared self-reinforced HDPE pipes with a three-layer structure combining spherical and shish-kebab crystals.Rotational processing aligned the molecular chains in the ring direction and formed shish-kebab crystals.As a result,the annular tensile strength of the rotationally processed three-layer shish-kebab structure(TSK)pipe increased from 26.7 MPa to 76.3 MPa,an enhancement of 185.8%.Notably,while maintaining excellent tensile strength(73.4 MPa),the elongation at break of the spherulite shishkebab spherulite(SKS)tubes was improved to 50.1%,as compared to 33.8%in the case of shish-kebab spherulite shish-kebab(KSK)tubes.This improvement can be attributed to the changes in the micro-morphology and polymer structure within the SKS tubes,specifically due to the formation of small-sized shish-kebab crystals and the low degrees of interlocking.In addition,2D-SAXS analysis revealed that KSK tubes have higher tensile strength due to smaller crystal sizes and larger shish dimensions,forming dense interlocking structures.In contrast,the SKS and TSK tubes had thicker amorphous regions and smaller shish sizes,resulting in reduced interlocking and mechanical performance.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 61763009 and 72172025)。
文摘Research on the self-similarity of multilayer networks is scarce, when compared to the extensive research conducted on the dynamics of these networks. In this paper, we use entropy to determine the edge weights in each sub-network,and apply the degree–degree distance to unify the weight values of connecting edges between different sub-networks, and unify the edges with different meanings in the multilayer network numerically. At this time, the multilayer network is compressed into a single-layer network, also known as the aggregated network. Furthermore, the self-similarity of the multilayer network is represented by analyzing the self-similarity of the aggregate network. The study of self-similarity was conducted on two classical fractal networks and a real-world multilayer network. The results show that multilayer networks exhibit more pronounced self-similarity, and the intensity of self-similarity in multilayer networks can vary with the connection mode of sub-networks.
基金supported by the National Natural Science Foundation of China(Grant Nos.62376089,62302153,62302154)the Key Research and Development Program of Hubei Province,China(Grant No.2023BEB024)+1 种基金the Young and Middle-Aged Scientific and Technological Innovation Team Plan in Higher Education Institutions in Hubei Province,China(Grant No.T2023007)the National Natural Science Foundation of China(Grant No.U23A20318).
文摘The Multilayer Perceptron(MLP)is a fundamental neural network model widely applied in various domains,particularly for lightweight image classification,speech recognition,and natural language processing tasks.Despite its widespread success,training MLPs often encounter significant challenges,including susceptibility to local optima,slow convergence rates,and high sensitivity to initial weight configurations.To address these issues,this paper proposes a Latin Hypercube Opposition-based Elite Variation Artificial Protozoa Optimizer(LOEV-APO),which enhances both global exploration and local exploitation simultaneously.LOEV-APO introduces a hybrid initialization strategy that combines Latin Hypercube Sampling(LHS)with Opposition-Based Learning(OBL),thus improving the diversity and coverage of the initial population.Moreover,an Elite Protozoa Variation Strategy(EPVS)is incorporated,which applies differential mutation operations to elite candidates,accelerating convergence and strengthening local search capabilities around high-quality solutions.Extensive experiments are conducted on six classification tasks and four function approximation tasks,covering a wide range of problem complexities and demonstrating superior generalization performance.The results demonstrate that LOEV-APO consistently outperforms nine state-of-the-art metaheuristic algorithms and two gradient-based methods in terms of convergence speed,solution accuracy,and robustness.These findings suggest that LOEV-APO serves as a promising optimization tool for MLP training and provides a viable alternative to traditional gradient-based methods.
基金the Shaanxi Provincial Key Research and Development Program(No.2020GY-040)。
文摘Design of a miniaturized lumped-element bandpass filter in multilayer liquid crystal polymer technology is proposed.Fractional bandwidth of the bandpass filter is 20%,operating at a center frequency of 500 MHz.In order to further reduce the size and improve the performance of the proposed filter,defected ground structure(DGS)has been implemented in the filter.Based on this structure,the volume of the inductor is reduced by 60%eficiently compared with the inductor without DGS,and the Q-factor is increased up to 257%compared with the traditional multilayer spiral inductor.The measured results indicate that the designed filter has a very sharp stopband,an insertion loss of 2.3dB,and a return loss of 18.6dB in the passband.The whole volume of the fabricated filter is 0.032入_(g)×0.05入_(g)×0.00075入_(g),where Ag is the guided wavelength of the center frequency.The proposed filter is easily integrated into radio-frequency/microwave circuitry at a low manufacturing cost,especially wireless communication.
基金supported by the National Natural Science Foundation of China(12064027,12464010)2022 Jiangxi Province High-level and Highskilled Leading Talent Training Project Selected(No.63)+1 种基金Jiujiang"Xuncheng Talents"(No.JJXC2023032)Jiujiang Natural Science Foundation Project(Key Technologies Research on Autonomous Cruise Solar-Powered UAV-2025-1).
文摘This study presents a wireless photovoltaic fault monitoring system integrating an STM32 microcontroller with an Improved Horned Lizard Optimization Algorithm(IHLOA)and a Multi-Layer Perceptron(MLP)neural network.The IHLOA algorithm introduces three key innovations:(1)chaotic initialization to enhance population diversity and global search capability,(2)adaptive random walk strategies to escape local optima,and(3)a cross-strategy mechanism to accelerate convergence and enhance fault detection accuracy and robustness.The system comprises both hardware and software components.The hardware includes sensors such as the BH1750 light intensity sensor,DS18B20 temperature sensor,and INA226 current and voltage sensor,all interfaced with the STM32F103C8T6 microcontroller and the ESP8266 module for wireless data transmission.The software,developed using QT Creator,incorporates an IHLOA-MLP model for fault diagnosis.The user-friendly interface facilitates intuitive monitoring and scalability for multiple systems.Experimental validation on a PV array demonstrates that the IHLOA-MLP model achieves a fault detection accuracy of 94.55%,which is 2.4%higher than the standard MLP,while reducing variance by 63.64%compared to the standard MLP.This highlights its accuracy and robustness.When compared to other optimization algorithms such as BKA-MLP(94.10%accuracy)and HLOA-MLP(94.00%accuracy),the IHLOA-MLP further reduces variance to 0.08,showcasing its superior performance.The system selects voltage as a feature vector to maintain circuit stability,avoiding efficiency impacts from series current sensors.This combined hardware and software approach further reduces false alarms to 0.1%through a consecutive-judgment mechanism,significantly enhancing practical reliability.This work provides a cost-effective and scalable solution for improving the stability and safety of PV systems in real-world applications.
基金The Natural Science Foundation of Liaoning Province of China(Grant No.2023-MSLH-314)he 2024 Yingkou Institute of Technology Campus level Scientific Research Project(FDL202408)+1 种基金The Foundation of Liaoning Provincial Key Laboratoryof Energy Storageand Utilization(GrantNo.CNNK202406)Yingkou Instituteof Technology campus level research project-Development of food additive supercriticalextraction equipment and fluid transmission systemresearch(Grant No.HX202427).
文摘Thermal conductivity is an important physical parameter in thermal equipment,in the blast furnace,rotary kiln and other equipment,multi-layer cylindrical wall is extremely important in industrial production of a thermal conductivity model,its thermal conductivity coefficient determines the ability of the cylindrical wall,which results in the existence of a large number of multi-layer cylinder thermal conductivity problems of the pitfalls.This paper focuses on the establishment of a mathematical model of the multi-layer cylinder thermal conductivity problem,by applying different voltages to the multi-layer cylinder wall,study the temperature distribution of the multi-layer cylinder wall under the conditions of natural convection and forced convection,and draw the line graphs under the conditions of natural convection and forced convection by Origin software,and finally conclude that:under the same conditions,the forced convection is significantly stronger than the natural convection;under the conditions of different voltages,the multi-layer cylinder wall under the conditions of steady state convection,the forced convection is much stronger than natural convection.Under different voltage conditions,the temperature of the multilayer cylinder wall under steady state conditions increases with the increase of voltage,which provides a strong support for the related research.
基金supported by the National Key R&D Program of China(2022YFA1305700 to Li J)the“Dawn”Program of Shanghai Education Commission,China(21SG33 to Li J)The National Natural Science Foundation of China(82272793 to Gao X).
文摘Objective:Prostate cancer(PCa)exhibits significant genomic differences between Western and Asian populations.This study aimed to design a predictive model applicable across diverse populations while selecting a limited set of genes suitable for clinical implementation.Methods:We utilized an integrated dataset of 1360 whole-exome and whole-genome sequences from Chinese and Western PCa cohorts to develop and evaluate the model.External validation was conducted using an independent cohort of patients.A graph neural network architecture,termed the pathway-aware multi-layered hierarchical network-Western and Asian(P-NETwa),was developed and trained on combined genomic profiles from Chinese and Western cohorts.The model employed a multilayer perceptron(MLP)to identify key signature genes from multiomics data,enabling precise prediction of PCa metastasis.Results:The model achieved an accuracy of 0.87 and an F1-score of 0.85 on Western population datasets.The application of integrated Chinese and Western population data improved the accuracy to 0.88,achieving an F1-score of 0.75.The analysis identified 18 signature genes implicated in PCa progression,including established markers(AR and TP53)and novel candidates(MUC16,MUC4,and ASB12).For clinical adoption,the model was optimized for commercially available gene panels while maintaining high classification accuracy.Additionally,a user-friendly web interface was developed to facilitate real-time prediction of primary versus metastatic status using the pre-trained P-NETwa-MLP model.Conclusion:The P-NETwa-MLP model integrates a query system that allows for efficient retrieval of prediction outcomes and associated genomic signatures via sample ID,enhancing its potential for seamless integration into clinical workflows.
文摘The outbreak of COVID-19 in 2019 has made people pay more attention to infectious diseases.In order to reduce the risk of infection and prevent the spread of infectious diseases,it is crucial to strengthen individual immunization measures and to restrain the diffusion of negative information relevant to vaccines at the opportune moment.This study develops a three-layer coupling model within the framework of hypernetwork evolution,examining the interplay among negative information,immune behavior,and epidemic propagation.Firstly,the dynamic topology evolution process of hypernetwork includes node joining,aging out,hyperedge adding and reconnecting.The three-layer communication model accounts for the multifaceted influences exerted by official media channels,subjective psychological acceptance capabilities,self-identification abilities,and physical fitness levels.Each level of the decision-making process is described using the Heaviside step function.Secondly,the dynamics equations of each state and the prevalence threshold are derived using the microscopic Markov chain approach(MMCA).The results show that the epidemic threshold is affected by three transmission processes.Finally,through the simulation testing,it is possible to enhance the intensity of official clarification,improve individual self-identification ability and physical fitness,and thereby promote the overall physical enhancement of society.This,in turn,is beneficial in controlling false information,heightening vaccination coverage,and controlling the epidemic.
基金the Deanship of Graduate Studies and Scientific Research at University of Bisha,Saudi Arabia for funding this research work through the Promising Program under Grant Number(UB-Promising-42-1445).
文摘Wind power forecasting plays a crucial role in optimizing the integration of wind energy into the grid by predicting wind patterns and energy output.This enhances the efficiency and reliability of renewable energy systems.Forecasting approaches inform energy management strategies,reduce reliance on fossil fuels,and support the broader transition to sustainable energy solutions.The primary goal of this study is to introduce an effective methodology for estimating wind power through temporal data analysis.This research advances an optimized Multilayer Perceptron(MLP)model using recently proposedmetaheuristic optimization algorithms,namely the FireHawk Optimizer(FHO)and the Non-Monopolize Search(NO).A modified version of FHO,termed FHONO,is developed by integrating NO as a local search mechanism to enhance the exploration capability and address the shortcomings of the original FHO.The developed FHONO is then employed to optimize the MLP for enhanced wind power prediction.The effectiveness of the proposed FHONO-MLP model is validated using renowned datasets from wind turbines in France.The results of the comparative analysis between FHONO-MLP,conventionalMLP,and other optimized versions of MLP show that FHONO-MLP outperforms the others,achieving an average RootMean Square Error(RMSE)of 0.105,Mean Absolute Error(MAE)of 0.082,and Coefficient of Determination(R^(2))of 0.967 across all datasets.These findings underscore the significant enhancement in predictive accuracy provided by FHONO and demonstrate its effectiveness in improving wind power forecasting.
基金Project supported by the National Natural Science Foundation of China (Grant No. 62371253)the Postgraduate Research and Practice Innovation Program of Jiangsu Province, China (Grant No. KYCX24_1179)。
文摘As the economy grows, environmental issues are becoming increasingly severe, making the promotion of green behavior more urgent. Information dissemination and policy regulation play crucial roles in influencing and amplifying the spread of green behavior across society. To this end, a novel three-layer model in multilayer networks is proposed. In the novel model, the information layer describes green information spreading, the physical contact layer depicts green behavior propagation, and policy regulation is symbolized by an isolated node beneath the two layers. Then, we deduce the green behavior threshold for the three-layer model using the microscopic Markov chain approach. Moreover, subject to some individuals who are more likely to influence others or become green nodes and the limitations of the capacity of policy regulation, an optimal scheme is given that could optimize policy interventions to most effectively prompt green behavior.Subsequently, simulations are performed to validate the preciseness and theoretical results of the new model. It reveals that policy regulation can prompt the prevalence and outbreak of green behavior. Then, the green behavior is more likely to spread and be prevalent in the SF network than in the ER network. Additionally, optimal allocation is highly successful in facilitating the dissemination of green behavior. In practice, the optimal allocation strategy could prioritize interventions at critical nodes or regions, such as highly connected urban areas, where the impact of green behavior promotion would be most significant.
