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The promotion of new energy vehicles (EVs) is an effective way to achieve low carbon emission reduction. This paper aims to investigate the optimal pricing of automotive supply chain members in the context of dual policy implementation while considering consumers' low-carbon preferences.

This article takes manufacturers, retailers and consumers in a main three-level supply chain as the research object. Stackelberg game theory is used as the theoretical guidance. A game model in which the manufacturer is the leader and the retailer is the follower is established. The author also considered the impact of carbon tax policies, subsidy policies and consumer preferences on the results. Furthermore, the author investigates the optimal decision-making problem under the profit maximization model.

Through model solving, it is found that the pricing of EVs is positively correlated with the unit price of carbon and the amount of subsidies. The following conclusions can be obtained by numerical analysis of each parameter. Changes in carbon prices have a greater impact on conventional gasoline vehicles. Based on the numerical analysis of parameter β, it is also found that when the government subsidizes consumers, supply chain members will increase their prices to obtain partial subsidies. Compared with retailers, low-carbon preferences have a greater impact on manufacturers.

The new energy automobile industry involves many policies, including tax cuts, tax exemptions and subsidies. The policy environment faced by the members of a supply chain is complex and diverse. Therefore, the analysis in this article is based only on partial policies.

The authors innovatively combine the three factors of subsidy policy, carbon tax policy and consumer low-carbon preference, with research on the pricing of EVs. The influence of policy factors and consumer preferences on the pricing of EVs is studied.

This paper aims to explore the factors impacting and influencing the consumer's decision to purchase honey in a retail store.

Data were collected from shopping mall intercepts in Perth, Western Australia, using a structured questionnaire. Exploratory factor analysis was used to identify the principal constructs which most influence the consumer's decision to purchase. On the basis of the ways in which honey was consumed within the household, cluster analysis was utilised to group the respondents into meaningful segments.

In Perth, Western Australia, honey is primarily consumed as a spread or a sweetener on breakfast cereals and porridge. However, honey is also used as a marinade, in cakes and cookies and as a beverage. According to the way in which honey is consumed in the household, five clusters were identified. In purchasing honey from a retail store, exploratory factor analysis revealed three principal constructs which were most influential in the consumer's decision to purchase: brand reputation, origin and value for money. Ethnicity was found to have a significant influence on the way in which honey was consumed in the household and the importance of the three constructs extracted.

This is one of the few studies that find a significant difference between Anglo Saxon and Asian consumers of honey.

Sulfate-reducing bacteria (SRB) are recognized by scholars as the most important class of bacteria leading to corrosion of metal materials. It is important to use the properties of microorganisms to inhibit the growth of SRB in the corrosion protection of metal materials and to protect the environment.

In this work, the behavior of anaerobic Thiobacillus denitrificans (TDN) intracellular enzyme inhibition of SRB corrosion of EH36 steel was investigated with electrochemical impedance spectroscopy, biological detection technology and X-ray photoelectron spectroscopy.

Results showed that the SRB crude intracellular enzyme affected the corrosion behavior of EH36 steel greatly and the purified TDN intracellular enzyme inhibits SRB intracellular enzyme corrosion to EH36 steel.

A perfect enzyme activity inhibition mechanism will provide theoretical guidance for the selection and application of anticorrosion microorganisms, which is of scientific significance in the field of microbial anticorrosion research.

This paper aims to contribute to the performance improvement and the broader application of hot-dip galvanized coating.

First, the ability to provide barrier protection, galvanic protection, and corrosion product protection provided by hot-dip galvanized coating is introduced. Then, according to the varying Fe content, the growth process of each sublayer within the hot-dip galvanized coating, as well as their respective microstructures and physical properties, is presented. Finally, the electrochemical corrosion behaviors of the different sublayers are analyzed.

The hot-dip galvanized coating is composed of η-Zn sublayer, ζ-FeZn13 sublayer, δ-FeZn10 sublayer, and Γ-Fe3Zn10 sublayer. Among these sublayers, with the increase in Fe content, the corrosion potential moves in a noble direction.

There is a lack of research on the corrosion behavior of each sublayer of hot-dip galvanized coating in different electrolytes.

It provides theoretical guidance for the microstructure control and performance improvement of hot-dip galvanized coatings.

The formation mechanism, coating properties, and corrosion behavior of different sublayers in hot-dip galvanized coating are expounded, which offers novel insights and directions for future research.

This paper aims to present the impact analysis of payload rendezvous with tethered satellite system and the design of an adaptive sliding mode controller which can deal with mass parameter uncertainty of targeted payload, so that the proposed cislunar transportation scheme with spinning tether system could be extended to a wider and more practical range.

In this work, dynamical model is first derived based on Langrangian equations to describe the motion of a spinning tether system in an arbitrary Keplerian orbit, which takes the mass of spacecraft, tether and payload into account. Orbital design and optimal open-loop control for the payload tossed by the spinning tether system are then presented. The real payload rendezvous impact around docking point is also analyzed. Based on reference acceleration trajectory given by optimal theories, a sliding mode controller with saturation functions is designed in the close-loop control of payload tossing stage under initial disturbance caused by actual rendezvous error. To alleviate the influence of inaccurate/unknown payload mass parameters, the adaptive law is designed and integrated into sliding mode controller. Finally, the performance of the proposed controller is evaluated using simulations. Simulation results validate that proposed controller is found effective in driving the spinning tether system to carry payload into desired cislunar transfer orbit and in dealing with payload mass parameter uncertainty in a relatively large range.

The results show that unideal rendezvous manoeuvres have significant impact on in-plane motion of spinning tether system, and the proposed adaptive sliding mode controller with saturation functions not only guarantees the stability but also provides good performance and robustness against the parameter and unstructured uncertainties.

This work addresses the analysis of actual impact on spinning tether system motion when payload is docking with system within tolerated docking window, rather than at the particular ideal docking point, and the robust tracking control of deep-space payload tossing missions with the spinning tether system using the adaptive sliding mode controller dealing with parameter uncertainties. This combination has not been proposed before for tracking control of multivariable spinning tether systems.

The obtained simulation structures could reflect the appearances and the features of the fabrics. The purpose of this paper is to promote a lot for design and manufacturing of weft-knitted lace fabrics (WKLF).

The advantages of WKLF compared with warp-knitted ones were displayed. The formation mechanism of the WKLF was analyzed with employing the mechanics principles. Spring-mass model was proposed in this paper to achieve the simulation of the fabrics. End mass points and intermediate mass points were involved in the model. The displacement of end mass points was considered the dominance and the foundation to settle the positions of all the mass points.

A novel jacquard lace style fabric with pattern-background effect knitted on circular knitting machine were put forward, which were different from the traditional lace fabrics manufactured on the warp knitting machines.

First, as the manufacturing equipment, circular knitting machine costs much less than warp knitting machine; second, the elastic performance along weft direction of WKLF is more excellent than that of warp-knitted ones. Third, the excellent extensibility gives nice comfort; furthermore, long floating threads do not exist on the WKLF surface, so that the snag will be avoided.

The purpose of this paper aims to investigate an effective algorithm for different types of disturbances rejection. New dynamics are designed based on disturbance. Observer-based sliding mode control (SMC) technique is used for approximation the disturbances as well as to stabilize the system effectively in presence of uncertainties.

This research work investigates the disturbances rejection algorithm for fixed-wing unmanned aerial vehicle. An algorithm based on SMC is introduced for disturbances rejection. Two types of disturbances are considered, the constant disturbance and the sinusoidal disturbance. The comprehensive lateral and longitudinal models of the system are presented. Two types of dynamics, the dynamics without disturbance and the new dynamics with disturbance, are presented. An observer-based algorithm is presented for the estimation of the dynamics with disturbances. Intensive simulations and experiments have been performed; the results not only guarantee the robustness and stability of the system but the effectiveness of the proposed algorithm as well.

In previous research work, new dynamics based on disturbances rejection are not investigated in detail; in this research work both the lateral and longitudinal dynamics with different disturbances are investigated.

As the stability is always important for flight, so the algorithm proposed in this research guarantees the robustness and rejection of disturbances, which plays a vital role in practical life for avoiding any kind of damage.

In the previous research work, new dynamics based on disturbances rejection are not investigated in detail; in this research work both the lateral and longitudinal dynamics with different disturbances are investigated. An observer-based SMC not only approximates the different disturbances and also these disturbances are rejected in order to guarantee the effectiveness and robustness.

The purpose of this paper is to introduce an improved system identification method for small unmanned helicopters combining adaptive ant colony optimization algorithm and Levy’s method and to solve the problem of low model prediction accuracy caused by low-frequency domain curve fitting in the small unmanned helicopter frequency domain parameter identification method.

This method uses the Levy method to obtain the initial parameters of the fitting model, uses the global optimization characteristics of the adaptive ant colony algorithm and the advantages of avoiding the “premature” phenomenon to optimize the initial parameters and finally obtains a small unmanned helicopter through computational optimization Kinetic models under lateral channel and longitudinal channel.

The algorithm is verified by flight test data. The verification results show that the established dynamic model has high identification accuracy and can accurately reflect the dynamic characteristics of small unmanned helicopter flight.

This paper presents a novel and improved frequency domain identification method for small unmanned helicopters. Compared with the conventional method, this method improves the identification accuracy and reduces the identification error.

The purpose of this paper is to propose a new aerodynamic parameter estimation methodology based on neural network and output error method, while the output error method is improved based on particle swarm algorithm.

Firstly, the algorithm approximates the dynamic characteristics of aircraft based on feedforward neural network. Neural network is trained by extreme learning machine, and the trained network can predict the aircraft response at (k + 1)th instant given the measured flight data at kth instant. Secondly, particle swarm optimization is used to enhance the convergence of Levenberg–Marquardt (LM) algorithm, and the improved LM method is used to substitute for the Gauss Newton algorithm in output error method. Finally, the trained neural network is combined with the improved output error method to estimate aerodynamic derivatives.

Neither depending on the initial guess of the parameters to be estimated nor requiring numerical integration of the aircraft motion equation, the proposed algorithm can be used for unstable aircraft and is successfully applied to extract aerodynamic derivatives from both simulated and real flight data.

The proposed method requires iterative calculation and can only identify parameters offline.

The proposed method is successfully applied to estimate aircraft aerodynamic parameters and can also be used as a new algorithm for other optimization problems.

In this study, the output error method is improved to reduce the dependence on the initial value of parameters and expand its application scope. It is applied in aircraft aerodynamic parameter identification together with neural network.

Bdellovibrio bacteriovorus is a gram-negative predatory bacterium which can potentially inhibit microbiologically influenced corrosion by preying on sulfate-reducing bacteria (SRB). However, no researches about the inhibition are reported according to the authors’ knowledge. The purpose of this paper was to investigate the Inhibition effect of B. bacteriovorus on the corrosion of X70 pipeline steel induced by SRB.

The effect of B. bacteriovorus on the growth of SRB was studied by measuring the optical density at 600 nm (OD600) and sulfate concentration in culture medium. X70 pipeline steel was used as the test material to investigate the anti-corrosion effect of B. bacteriovorus on SRB by conducting electrochemical analysis (including Tafel polarization curves and electrochemical impendence spectroscopy) and weight loss measurement.

B. bacteriovorus could inhibit the growth of SRB in culture medium by its predation on SRB, which led to decrease of OD600 value and increase of sulfate concentration. The results of electrochemical analysis indicated that B. bacteriovorus had positive inhibition efficiencies on SRB-induced corrosion of X70 pipeline steel. Moreover, corrosion rate of X70 pipeline steel was declined from 19.17 to 3.75 mg·dm-2·day-1 by the presence of B. bacteriovorus.

This is the first report about using B. bacteriovorus to inhibit the corrosion induced by SRB. Compared to other anti-corrosion methods, the microbial inhibition methods exhibit more considerable application value due to its low cost, high efficiency and non-pollution.