A Novel Method for Aging Prediction of Railway Catenary Based on Improved Kalman Filter

The aging prediction of railway catenary is of profound significance for ensuring the regular operation of electrified trains.However,in real-world scenarios,accurate predictions are challenging due to various interferences.This paper addresses this challenge by proposing a novel method for predicting the aging of railway catenary based on an improved Kalman filter(KF).The proposed method focuses on modifying the priori state estimate covariance and measurement error covariance of the KF to enhance accuracy in complex environments.By comparing the optimal displacement value with the theoretically calculated value based on the thermal expansion effect of metals,it becomes possible to ascertain the aging status of the catenary.To improve prediction accuracy,a railway catenary aging prediction model is constructed by integrating the Takagi-Sugeno(T-S)fuzzy neural network(FNN)and KF.In this model,an adaptive training method is introduced,allowing the FNN to use fewer fuzzy rules.The inputs of the model include time,temperature,and historical displacement,while the output is the predicted displacement.Furthermore,the KF is enhanced by modifying its prior state estimate covariance and measurement error covariance.These modifications contribute to more accurate predictions.Lastly,a low-power experimental platform based on FPGA is implemented to verify the effectiveness of the proposed method.The test results demonstrate that the proposed method outperforms the compared method,showcasing its superior performance.

Effect of Thermal-cold Cycling Treatment on Mechanical Properties and Microstructure of 6061 Aluminum Alloy

The influence of thermal-cold cycling treatment on mechanical properties and microstructure of 6061 aluminum alloy was investigated by means of tensile test, optical microscopy(OM), X-ray diffraction(XRD) and transmission electron microscopy(TEM). The cryogenic treatment mechanism of the alloys was discussed. The results show that thermal-cold cycling treatment is beneficial since it produces a large number of dislocations and accelerates the ageing process of the alloy and yields the finer dispersed β" precipitates in the matrix. This variation of microstructural changes leads to more favorable mechanical properties than the other investigated states, while grain boundary precipitation is coarse and distributed discontinuously along grain boundaries, with a lower precipitation free zone(PEZ) on the both sides of precipitated phase. As a result, the tensile strength, elongation and conductivity of 6061 aluminum alloy after thermal-cold cycling treatment are 373.37 MPa, 17.2% and 28.2 MS/m, respectively. Compared with conventional T6 temper, the mechanical properties are improved significantly.

Development strategies of leisure agriculture and rural tourism of Henan province based on industry convergence

The industrial convergence has developed rapidly,which benefit promoting the innovation of traditional industry and optimizing the industrial structure.The integration of agriculture and tourism can promote the development of agricultural economy and tourism economy.Based on the industrial convergence theory,this paper explains the necessity of convergence of leisure agriculture and rural tourism,and studies on the status quo of the development of tourism resources in Henan.Finally,it put forward the development strategies:(1)more support from the government is in need on policy,finance and using rural area;(2)the rural planning needs to be strengthened;(3)the agricultural resources needs to be integrated;(4)the incentive system needs to be built to attract talent.

Cross-Sectional Associations of Lifestyle Behaviors with Depressive Symptoms in Adolescents

This study aimed to examine the associations between lifestyle behaviors and depressive symptoms in adolescents.Self-reported data from the 2019 Youth Risk Behavior Survey(YRBS)was analyzed.Depressive symptoms were set as the outcome variable.Movement variables(physical activity,muscle-strengthening exercise,physical education attendance,sports team participation,television watching,video or computer games,and sleep),eating behaviors(fruit intake,vegetable intake,milk intake,and eating breakfast or not),and substance use(alcohol use and cigarette use)were included as explanatory variables.Binary logistic regression was used to explore the asso-ciations between lifestyle behaviors and depressive symptoms after adjusting for sex,age,grade,race,and weight status.Of 13,677 participants who completed the investigation,girls were more than boys(50.3%vs.48.6%).The proportion of participants in grades 9,10,11,and 12 was 26.6,27.2,24.3,and 20.8,respectively.Of them,the prevalence of depressive symptoms was 36.0%(weighted%:36.7%[35.1%,38.3%]).Among all the lifestyle behaviors included,participating in no sports teams(OR=1.53[1.32,1.77]),spending more than 2 h in video or computer games(OR=1.64[1.40,1.92]),sleeping less than 8 h nightly(OR=1.79[1.45,2.20]),not eating breakfast(OR=1.56[1.37,1.78]),alcohol use(OR=1.74[1.49,2.02]),and cigarette use(OR=1.83[1.42,2.37])were associated with higher odds of depressive symptoms.To reduce depressive symptoms in adolescents,interventions can consider encouraging adolescents to engage in team sports activity,limit time for video or com-puter games,sleep enough,regularly eat breakfast,and avoid using alcohol and cigarette.Future studies are encouraged to verify our researchfindings by using a more improved study design.

Optimization of Chiller Loading Problem Using Improved Golden Jackal Optimization Algorithm Leads to Reduction in Energy Consumption

This paper proposes a modified golden jackal optimization(IGJO)algorithm to solve the OCL(which stands for optimal cooling load)problem to minimize energy consumption.In this algorithm,many tools have been developed,such as numerical visualization,local field method,competitive selectionmethod,and iterative strategy.The IGJO algorithm is used to improve the research capabilities of the algorithm in terms of global tuning and rotation speed.In order to fully utilize the effectiveness of the proposed algorithm,three famous examples of OCL problems in basic ventilation systems were studied and compared with some previously published works.The results show that the IGJO algorithm can find solutions equal to or better than other methods.Underpinning these studies is the need to reduce energy consumption in air conditioning systems,which is a critical business and environmental decision.The Optimal Chiller Load(OCL)problem is well-known in the industry.It is the best method of operation for the refrigeration plant to satisfy the requirement of cooling.In order to solve the OCL problem,an improved Golden Jackal optimization algorithm(IGJO)was proposed.The IGJO algorithm consists of a number of parts to improve the global optimization and rotation speed.These studies are intended to address more effectively the issue of OCL,which results in energy savings in air-conditioning systems.The performance of the proposed IGJO algorithm is evaluated,and the results are compared with the results of three known OCL problems in the ventilation system.The results indicate that the IGJO method has the same or better optimization ability as other methods and can improve the energy efficiency of the system’s cold air.

IRS Assisted UAV Communications against Proactive Eavesdropping in Mobile Edge Computing Networks

In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of UAV,the transmitting beamforming of users,and the phase shift matrix of IRS.The original problem is strong non-convex and difficult to solve.We first propose two basic modes of the proactive eavesdropper,and obtain the closed-form solution for the boundary conditions of the two modes.Then we transform the original problem into an equivalent one and propose an alternating optimization(AO)based method to obtain a local optimal solution.The convergence of the algorithm is illustrated by numerical results.Further,we propose a zero forcing(ZF)based method as sub-optimal solution,and the simulation section shows that the proposed two schemes could obtain better performance compared with traditional schemes.

Energy Efficiency Maximization in Mobile Edge Computing Networks via IRS assisted UAV Communications

In this paper,we investigate the energy efficiency maximization for mobile edge computing(MEC)in intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)communications.In particular,UAVcan collect the computing tasks of the terrestrial users and transmit the results back to them after computing.We jointly optimize the users’transmitted beamforming and uploading ratios,the phase shift matrix of IRS,and the UAV trajectory to improve the energy efficiency.The formulated optimization problem is highly non-convex and difficult to be solved directly.Therefore,we decompose the original problem into three sub-problems.We first propose the successive convex approximation(SCA)based method to design the beamforming of the users and the phase shift matrix of IRS,and apply the Lagrange dual method to obtain a closed-form expression of the uploading ratios.For the trajectory optimization,we propose a block coordinate descent(BCD)based method to obtain a local optimal solution.Finally,we propose the alternating optimization(AO)based overall algorithmand analyzed its complexity to be equivalent or lower than existing algorithms.Simulation results show the superiority of the proposedmethod compared with existing schemes in energy efficiency.

Constraints Separation Based Evolutionary Multitasking for Constrained Multi-Objective Optimization Problems

Constrained multi-objective optimization problems(CMOPs)generally contain multiple constraints,which not only form multiple discrete feasible regions but also reduce the size of optimal feasible regions,thus they propose serious challenges for solvers.Among all constraints,some constraints are highly correlated with optimal feasible regions;thus they can provide effective help to find feasible Pareto front.However,most of the existing constrained multi-objective evolutionary algorithms tackle constraints by regarding all constraints as a whole or directly ignoring all constraints,and do not consider judging the relations among constraints and do not utilize the information from promising single constraints.Therefore,this paper attempts to identify promising single constraints and utilize them to help solve CMOPs.To be specific,a CMOP is transformed into a multitasking optimization problem,where multiple auxiliary tasks are created to search for the Pareto fronts that only consider a single constraint respectively.Besides,an auxiliary task priority method is designed to identify and retain some high-related auxiliary tasks according to the information of relative positions and dominance relationships.Moreover,an improved tentative method is designed to find and transfer useful knowledge among tasks.Experimental results on three benchmark test suites and 11 realworld problems with different numbers of constraints show better or competitive performance of the proposed method when compared with eight state-of-the-art peer methods.

Adaptive H_(∞)Filtering Algorithm for Train Positioning Based on Prior Combination Constraints

To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.

Multiobjective Differential Evolution for Higher-Dimensional Multimodal Multiobjective Optimization

In multimodal multiobjective optimization problems(MMOPs),there are several Pareto optimal solutions corre-sponding to the identical objective vector.This paper proposes a new differential evolution algorithm to solve MMOPs with higher-dimensional decision variables.Due to the increase in the dimensions of decision variables in real-world MMOPs,it is diffi-cult for current multimodal multiobjective optimization evolu-tionary algorithms(MMOEAs)to find multiple Pareto optimal solutions.The proposed algorithm adopts a dual-population framework and an improved environmental selection method.It utilizes a convergence archive to help the first population improve the quality of solutions.The improved environmental selection method enables the other population to search the remaining decision space and reserve more Pareto optimal solutions through the information of the first population.The combination of these two strategies helps to effectively balance and enhance conver-gence and diversity performance.In addition,to study the per-formance of the proposed algorithm,a novel set of multimodal multiobjective optimization test functions with extensible decision variables is designed.The proposed MMOEA is certified to be effective through comparison with six state-of-the-art MMOEAs on the test functions.

A New Method of Wind Turbine Bearing Fault Diagnosis Based on Multi-Masking Empirical Mode Decomposition and Fuzzy C-Means Clustering

Based on Multi-Masking Empirical Mode Decomposition (MMEMD) and fuzzy c-means (FCM) clustering, a new method of wind turbine bearing fault diagnosis FCM-MMEMD is proposed, which can determine the fault accurately and timely. First, FCM clustering is employed to classify the data into different clusters, which helps to estimate whether there is a fault and how many fault types there are. If fault signals exist, the fault vibration signals are then demodulated and decomposed into different frequency bands by MMEMD in order to be analyzed further. In order to overcome the mode mixing defect of empirical mode decomposition (EMD), a novel method called MMEMD is proposed. It is an improvement to masking empirical mode decomposition (MEMD). By adding multi-masking signals to the signals to be decomposed in different levels, it can restrain low-frequency components from mixing in highfrequency components effectively in the sifting process and then suppress the mode mixing. It has the advantages of easy implementation and strong ability of suppressing modal mixing. The fault type is determined by Hilbert envelope finally. The results of simulation signal decomposition showed the high performance of MMEMD. Experiments of bearing fault diagnosis in wind turbine bearing fault diagnosis proved the validity and high accuracy of the new method.

Simple Fabrication of Hierarchical Micro/Nanostructure Superhydrophobic Surface with Stable and Superior Anticorrosion Silicon Steel via Laser Marking Treatment

To improve the weak corrosion resistance of silicon steel to acid solution and alkaline solution with high temperature,a stable hierarchical micro/nanostructure superhydrophobic surface with myriad irregular micro-scale hump and sheet-like nanostructure was successfully prepared on silicon steel by a simple,efficient and facile operation in large-area laser marking treatment.The morphology,composition,wettability of the as-prepared surface were studied.The superhydrophobic performance of the surface was investigated as well.Additionally,the corrosion resistance of the superhydrophobic surface to acidic solutions at room temperature and alkaline solutions at high temperature (80 ℃) was carefully explored.The corrosion resistance mechanism was clarified.Moreover,considering the practical application of the surface in the future,the hardness of the hierarchical micro/nanostructure superhydrophobic surface was studied.The experimental results indicate that the hierarchical micro/nanostructure surface with texture spacing of 100 μm treated at laser scanning speed of 100 mms/ presents superior superhydrophobicity after decreasing surface energy.The contact angle can be as high as 156.6°.Additionally,the superhydrophobic surface provide superior and stable anticorrosive protection for silicon steel in various corrosive environments.More importantly,the prepared structure of the surface shows high hardness,which ensures that the surface of the superhydrophobic surface cannot be destroyed easily.The surface is able to maintain great superhydrophobic performance when it suffers from slight impacting and abrasion.

Corrosion and Electrochemical Behavior of Zn-Cu-Ti Alloy Added with La in 3% NaOH Solution

The corrosion mechanism of Zn-Cu-Tialloy added with La in 3% NaOH solution was investigated by electrochemicaltesting and SEM observation.Polarization curves manifested that the overallcorrosion kinetics of alloys are under anodic control.The anodic passivation of the Zn-Cu-Tialloy is remarkably improved by the addition of La.Because La can effectively improve the hydrogen evolution/oxygen reduction over-potentialof alloy elements,and the rare earth oxide film plays an important role in insulation that can strengthen the dielectric properties of Zn-Cu-Tialloy,the corrosion resistance of Zn-Cu-Tialloy is made significantly better by adding a trace amount of La.The improvement of corrosion resistance is not positively correlated with the adding amount of La to alloy.The Zn-Cu-Ti-0.5La alloy displays the best corrosion resistance behavior.The corrosion form of the alloys mainly belongs to a selective corrosion and the main solid corrosion products are Zn（OH）_2 and ZnO.

Cosmos and Taxis in the Construction of Social Order A Case Study of Law,Legislation and Liberty

This paper explains and analyzes the tw o kinds of order,including cosm os( endogenous order) and taxis( exogenous order),which play a fundamental and essential role in the process of social order construction.Based on these tw o kinds of order,it presents the rule theory that supports freedom and thereafter puts forw ard the ideas,rules and system s of constructing social freedom.T o a large extent,H ayek's social order is in essence a free order.T his analysis of freedom has a very im portant guiding value for the research and developm ent of m odern social theory and the structure of free order.

Magnetic and electronic properties of two-dimensional metal-organic frameworks TM_(3)(C_(2)NH)_(12)

The ferromagnetism of two-dimensional(2D)materials has aroused great interest in recent years,which may play an important role in the next-generation magnetic devices.Herein,a series of 2D transition metal-organic framework materials(TM-NH MOF,TM=Sc-Zn)are designed,and their electronic and magnetic characters are systematically studied by means of first-principles calculations.Their structural stabilities are examined through binding energies and ab-initio molecular dynamics simulations.Their optimized lattice constants are correlated to the central TM atoms.These 2D TM-NH MOF nanosheets exhibit various electronic and magnetic performances owing to the effective charge transfer and interaction between TM atoms and graphene linkers.Interestingly,Ni-and Zn-NH MOFs are nonmagnetic semiconductors(SM)with band gaps of 0.41 eV and 0.61 eV,respectively.Co-and Cu-NH MOFs are bipolar magnetic semiconductors(BMS),while Fe-NH MOF monolayer is a half-semiconductor(HSM).Furthermore,the elastic strain could tune their magnetic behaviors and transformation,which ascribes to the charge redistribution of TM-3d states.This work predicts several new 2D magnetic MOF materials,which are promising for applications in spintronics and nanoelectronics.

Ab initio study on crystal structure and phase stability of ZrC_(2) under high pressure

The structural stabilities and crystal evolution behaviors of the hyper stoichiometric compound ZrC_(2)(carbon rich;C/Zr> 1.0) are studied under ambient and high pressure conditions using first-principles calculations in combination with the particle-swarm optimization algorithm.Six viable structures of ZrC_(2) in P21/c,Cmmm,Cmc2_(1),P4_(2)/nmc,Immm and P6/mmm symmetries are identified.These structures are dynamically stable as their phonon spectra have no imaginary modes at zero pressure or at the selected high-pressure points.Among them,the P21/c phase represents the ground state structure,whereas P21/c,P4_(2)/nmc,Immm and P6/mmm phases are part of the phase transition series.The phase order and critical pressures of the phase transition are determined to be approximately 300 GPa according to the equation of states and enthalpy.Furthermore,the mechanical and electronic properties are investigated.The P21/c and Cmc2_(1) phases display a semi-metal nature,whereas the P4_(2)/nmc,Immm,P6/mmm and Cmmm phases exhibit a metallic nature.Moreover,the present study reveals considerable information regarding the structural,mechanical and electronic properties of ZrC_(2),thereby providing key insights into its material properties and evaluating its behavior in practical applications.

Strain-tunable electronic and optical properties of h-BN/BC_(3)heterostructure with enhanced electron mobility

By using first-principles calculation,we study the properties of h-BN/BC_(3)heterostructure and the effects of external electric fields and strains on its electronic and optical properties.It is found that the semiconducting h-BN/BC_(3)has good dynamical stability and ultrahigh stiffness,enhanced electron mobility,and well-preserved electronic band structure as the BC_(3)monolayer.Meanwhile,its electronic band structure is slightly modified by an external electric field.In contrast,applying an external strain can mildly modulate the electronic band structure of h-BN/BC_(3)and the optical property exhibits an apparent redshift under a compressive strain relative to the pristine one.These findings show that the h-BN/BC_(3)hybrid can be designed as optoelectronic device with moderately strain-tunable electronic and optical properties.

Negative self-feedback induced enhancement and transition of spiking activity for class-3 excitability

Post-inhibitory rebound(PIR)spike,which has been widely observed in diverse nervous systems with different physiological functions and simulated in theoretical models with class-2 excitability,presents a counterintuitive nonlinear phenomenon in that the inhibitory effect can facilitate neural firing behavior.In this study,a PIR spike induced by inhibitory stimulation from the resting state corresponding to class-3 excitability that is not related to bifurcation is simulated in the Morris–Lecar neuron.Additionally,the inhibitory self-feedback mediated by an autapse with time delay can evoke tonic/repetitive spiking from phasic/transient spiking.The dynamical mechanism for the PIR spike and the tonic/repetitive spiking is acquired with the phase plane analysis and the shape of the quasi-separatrix curve.The result extends the counterintuitive phenomenon induced by inhibition to class-3 excitability,which presents a potential function of inhibitory autapse and class-3 neuron in many neuronal systems such as the auditory system.

Electronic and optical properties of 3N-doped graphdiyne/MoS_(2) heterostructures tuned by biaxial strain and external electric field

The construction of van der Waals(vdW)heterostructures by stacking different two-dimensional layered materials have been recognised as an effective strategy to obtain the desired properties.The 3N-doped graphdiyne(N-GY)has been successfully synthesized in the laboratory.It could be assembled into a supercapacitor and can be used for tensile energy storage.However,the flat band and wide forbidden bands could hinder its application of N-GY layer in optoelectronic and nanoelectronic devices.In order to extend the application of N-GY layer in electronic devices,MoS_(2) was selected to construct an N-GY/MoS_(2) heterostructure due to its good electronic and optical properties.The N-GY/MoS_(2) heterostructure has an optical absorption range from the visible to ultraviolet with a absorption coefficient of 10^(5) cm^(-1).The N-GY/MoS_(2) heterostructure exhibits a type-II band alignment allows the electron–hole to be located on N-GY and MoS_(2) respectively,which can further reduce the electron–hole complexation to increase exciton lifetime.The power conversion efficiency of N-GY/MoS_(2) heterostructure is up to 17.77%,indicating it is a promising candidate material for solar cells.In addition,the external electric field and biaxial strain could effectively tune the electronic structure.Our results provide a theoretical support for the design and application of N-GY/MoS_(2) vdW heterostructures in semiconductor sensors and photovoltaic devices.

ANALYSIS OF DYNAMICAL BUCKLING AND POST BUCKLING FOR BEAMS BY FINITE SEGMENT METHOD

Based on the multi-rigid body discretization model, namely, finite segment model,a chain multi-rigid-body-hinge-spring system model of a beam was presented, then a nonlinear parametrically exacted vibration equation of multi-degrees of freedom system was established using the coordination transformation method, and its resonance fields were derived by the restriction parameter method, that is, the dynamical buckling analysis of the beam. Because the deformation of a beam is not restricted by the discrete model and dynamic equation, the post buckling analysis can be done in above math model. The numerical solutions of a few examples were obtained by direct integrated method, which shows that the mechanical and math model gotten is correct.