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Sensorless interior permanent magnet in-wheel motor (IPMIWM), as an exemplar of modular automation system, has attracted considerable interests in recent years. This paper aims to investigate a novel hybrid control approach for the sensorless IPMIWM from a cyber-physical systems (CPS) perspective.

The control approach is presented based on the hybrid dynamical theory. In the standstill-low (S-L) speed, the rotor position/speed signal is estimated by the method of the high frequency (HF) voltage signal injection. The least square support vector machine (LS-SVM) is used to acquire the rotor position/speed signal in medium-high (M-H) speed operation. Hybrid automata model of the IPMIWM is established due to its hybrid dynamic characteristics in wide speed range. A hybrid state observer (HSO), including a discrete state observer (DSO) and a continuous state observer (CSO), is designed for rotor position/speed estimation of the IPMIWM.

The hardware-in-the-loop testing based on dSPACE is carried out on the test bench. Experimental investigations demonstrate the hybrid control approach can not only identify the rotor position/speed signal with a certain load but also be able to reject the load disturbance. The reliability and the effectiveness of the proposed hybrid control approach were verified.

The proposed hybrid control approach for the sensorless IPMIWM promotes the deep combination and coordination of sensorless IPMIWM drive system. It also theoretically supports and extends the development of the hybrid control of the highly integrated modular automation system.

The paper aims to clarify the influence of different picture contents on consumer's willingness to click pictures when shopping for agricultural products online and examine the intermediary mechanism and boundary conditions of the impact.

The paper opted for an empirical study based on the cue utilization theory and information processing theory, including three experiments to test the existence, intermediary mechanism and boundary conditions of the impact of online picture contents of agricultural products on consumers' clicking intention.

The paper provides empirical insights about the influence of picture contents on consumer's willingness to click when shopping for agricultural products online. The picture of product's production environment or grower on the search result page can effectively improve consumer's willingness to click the product under dual systemic information processing modes. Compared with product pictures, pictures displaying products and production environment can stimulate more cognitive system processing, and pictures displaying products and its growers can stimulate more emotional system processing, both resulting in higher click intention. However, the above effects only exist in the context of non-branded agricultural products.

The research results not only provide practical guidance for merchants, but also fill the gap in the research on the impact of picture contents on consumers in the field of agricultural products in online marketing.

The paper aims to clarify the influence of different picture contents on consumer's willingness to click pictures when shopping for agricultural products online and examine the intermediary mechanism and boundary conditions of the impact.

The paper opted for an empirical study based on the cue utilization theory and information processing theory, including 3 experiments to test the existence, intermediary mechanism and boundary conditions of the impact of online picture contents of agricultural products on consumers' clicking intention.

The paper provides empirical insights about the influence of picture contents on consumer's willingness to click when shopping for agricultural products online. The picture of product's production environment or grower on the search result page can effectively improve consumer's willingness to click the product under dual-systemic information processing modes. Compared with product pictures, pictures displaying products and production environment can stimulate more cognitive system processing, and pictures displaying products and its growers can stimulate more emotional system processing, both resulting in higher click intention. However, the above effects only exist in the context of non-branded agricultural products.

The research results can not only provide practical guidance for merchants, but also fill the gap in the research on the impact of picture contents on consumers in the field of agricultural products in online marketing.

Given the fact that the income disparity has become extremely severe in rural China, the purpose of this paper is to examine heterogeneity in food consumption among various income classes and to investigate the impact of changes in income distribution patterns on food demand in rural China.

In this study, the authors partition the households into five income classes according to the distribution of household per capita net income. Using household data drawn from the China Health and Nutrition Survey in 2011, a two-stage demand model is applied to estimate a food demand system for each of the income classes. After obtaining the estimated income elasticities of eight studied food groups for each income class, the authors then examine the responsiveness of food demand to the changes in income distribution by means of four scenarios with varying income distribution.

The empirical results indicate that substantial differences in food consumption exist across various income classes. Specifically, the lowest-income households are more sensitive to price and income changes for most studied food groups than the highest-income households are. In general, income responsiveness is higher for meats, aquatic products and dairy products. Based on estimated income elasticities, the projected food consumption under different income distribution patterns shows that changes in income distribution have significant influences on food consumption. In addition, the authors conclude that a more equal distribution of income would be associated with a higher demand for food in rural China.

This paper employs a two-stage demand model to estimate food demand in rural China by income classes. The results imply substantial differences in food demand for various income classes. Therefore, income distribution should be taken into account instead of an average estimation for the population as a whole when investigating food demand in rural China. Given the significant changes in income distribution in rural China, this study provides several important policy implications to alleviate income inequality and poverty, as well as to improve nutrition for lower-income classes.

Historic districts are faced with inadequate features protection and landscape destruction in the process of accelerating urban construction, urban design focuses on how places function in addition to how they look, this theory is suitable for the protection of historical districts. At the present stage, the traditional urban design of historical districts has a series of problems, such as uncomprehensive research about characteristics, incomplete workflow and the lack of transformation route from design scheme to implementation, the main reason is that there is a mismatch between the setting goal and planning implementation. Urban design based on “Action planning” has the characteristics of comprehensive research contents, specific implementation plans and complete workflow, it arranges the workflow with four stages, including design preparation, design planning, design implementation and design evaluation, which is a new exploration and attempt to turn traditional blueprint-oriented into action-oriented. Urban design of North Shuncheng Lane Historic Districts in Xi'an city used action planning as a concept and established an framework including “identify development status and problems—construct action target and strategy—determine action projects and specific plans—improve and evaluate the results”, to implement design ideas into practice and to guide the protection of historic districts. Above all, action-oriented planning is considered the key to the development of historic districts.

This study aims to fabricate and manipulate ensemble spin of negative nitrogen-vacancy (NV⁻) centres optimally for future solid atomic magnetometers/gyroscope. Parameters for sample preparation most related to magnetometers/gyroscope are, in particular, the concentration and homogeneity of the NV⁻ centres, the parameters’ microwave antenna of resonance frequency and the strength of the microwave on NV⁻ centres. Besides, the abundance of other impurities such as neutral NV centres (NV⁰) and substitutional nitrogen in the lattice also plays a critical role in magnetic sensing.

The authors succeeded in fabricating the assembly of NV centres in diamond and they determined its concentration of (2-3) × 10¹⁶ cm⁻³ with irradiation followed by annealing under a high temperature condition. They explored a novel magnetic resonance approach to detect the weak magnetic fields that takes advantage of the solid-state electron ensemble spin of NV⁻ centres in diamond. In particular, the authors set up a magnetic sensor on the basis of the assembly of NV centres. They succeeded in fabricating the assembly of NV centres in diamond and determined its concentration. They also clarified the magnetic field intensity measured at different positions along the antenna with different lengths, and they found the optimal position where the signal of the magnetic field reaches the maximum.

The authors mainly reported preparation, initialization, manipulation and measurement of the ensemble spin of the NV centres in diamond using optical excitation and microwave radiation methods with variation of the external magnetic field. They determined the optimal parameters of irradiation and annealing to generate the ensemble NV centres, and a concentration of NV⁻ centres as high as 10¹⁶ cm⁻³ in diamond was obtained. In addition, they found that sensitivity of the magnetometer using this method can reach as low as 5.22 µT/Hz currently.

This research can shed light on the development of an atomic magnetometer and a gyroscope on the basis of the ensemble spin of NV centres in diamond.

High concentration spin of NV⁻ in diamond is one of the advantages compared with that of the atomic vapor cells, because it can obtain a higher concentration. When increasing the spin concentration, the spin signal is easy to detect, and macro-atomic spin magnetometer become possible. This research is the first step for solid atomic magnetometers with high spin density and high sensitivity potentially with further optimization. It has a wide range of applications from fundamental physics tests, sensor applications and navigation to detection of NMR signals.

As has been pointed out, in this research, the authors mainly worked on fabricating NV⁻ centres with high concentration (10¹⁵-10¹⁶ cm⁻³) in diamond by using optimal irradiation and annealing processes, and they quantitatively defined the NV⁻ concentration, which is important for the design of higher concentration processes in the magnetometer and gyroscope. Until now, few groups can directly define the NV⁻ concentration. Besides, the authors optimized the microwave antenna parameters experimentally and explored the dependence between the splitting of the magnetic resonance and the magnetic fields, which dictated the minimum detectable magnetic field.

Studies on developed economies showed that imposing taxes on animal-based foods could effectively reduce agricultural greenhouse gas emissions (AGHGEs), while this taxation may not be appropriate in developing countries due to the complex nutritional status across income classes. Hence, this study aims to explore optimal tax rate levels considering both emission reduction and nutrient intake, and examine the heterogenous effects of taxation across various income classes in urban and rural China.

The authors estimated the Quadratic Almost Ideal Demand System model to calculate the price elasticities for eight food groups, and performed three simulations to explore the relative optimal tax regions via the relationships between effective animal protein intake loss and AGHGE reduction by taxes.

The results showed that the optimal tax rate bands can be found, depending on the reference levels of animal protein intake. Designing taxes on beef, mutton and pork could be a preliminary option for reducing AGHGEs in China, but subsidy policy should be designed for low-income populations at the same time. Generally, urban residents have more potential to reduce AGHGEs than rural residents, and higher income classes reduce more AGHGEs than lower income classes.

This study fills the gap in the literature by developing the methods to design taxes on animal-based foods from the perspectives of both nutrient intake and emission reduction. This methodology can also be applied to analyze food taxes and GHGE issues in other developing countries.

Semantic modelling is an essential prerequisite for designing the intelligent human–computer interaction in future aircraft cockpit. The purpose of this paper is to outline an ontology-based solution to this issue.

The scenario elements are defined considering the cognitive behaviours, system functions, interaction behaviours and interaction situation. The knowledge model consists of a five-tuple array including concepts, relations, functions, axioms and instances. Using the theory of belief-desire-intention, the meta-model of cognitive behaviours is established. The meta-model of system functions is formed under the architecture of sub-functions. Supported by information flows, the meta-model of interaction behaviours is presented. Based on the socio-technical characteristics, the meta-model of interaction situation is proposed. The knowledge representation and reasoning process is visualized with the semantic web rule language (SWRL) on the Protégé platform. Finally, verification and evaluation are carried out to assess the rationality and quality of the ontology model. Application scenarios of the proposed modelling method are also illustrated.

Verification results show that the knowledge reasoning based on SWRL rules can further enrich the knowledge base in terms of instance attributes and thereby improve the adaptability and learning ability of the ontology model in different simulations. Evaluation results show that the ontology model has a good quality with high cohesion and low coupling.

The approach presented in this paper can be applied to model complex human–machine–environment systems, from a semantics-driven perspective, especially for designing future cockpits.

Different from the traditional approaches, the method proposed in this paper tries to deal with the socio-technical modelling issues concerning multidimensional information semantics. Meanwhile, the constructed model has the ability of autonomous reasoning to adapt to complex situations.

This paper aims to introduce a novel four-dimensional hyper-chaotic system with different hyper-chaotic attractors as certain parameters vary. The typical dynamical behaviors of the new hyper-chaotic system are discussed in detail. The control problem of these hyper-chaotic attractors is also investigated analytically and numerically. Then, two novel electronic circuits of the proposed hyper-chaotic system with different parameters are presented and realized using physical components.

The adaptive control method is derived to achieve chaotic synchronization and anti-synchronization of the novel hyper-chaotic system with unknown parameters by making the synchronization and anti-synchronization error systems asymptotically stable at the origin based on Lyapunov stability theory. Then, two novel electronic circuits of the proposed hyper-chaotic system with different parameters are presented and realized using physical components. Multisim simulations and electronic circuit experiments are consistent with MATLAB simulation results and they verify the existence of these hyper-chaotic attractors.

Comparisons among MATLAB simulations, Multisim simulation results and physical experimental results show that they are consistent with each other and demonstrate that changing attractors of the hyper-chaotic system exist.

The goal of this paper is to construct a new four-dimensional hyper-chaotic system with different attractors as certain parameters vary. The adaptive synchronization and anti-synchronization laws of the novel hyper-chaotic system are established based on Lyapunov stability theory. The corresponding electronic circuits for the novel hyper-chaotic system with different attractors are also implemented to illustrate the accuracy and efficiency of chaotic circuit design.

Since many global path planning algorithms cannot achieve the planned path with both safety and economy, this study aims to propose a path planning method for unmanned vehicles with a controllable distance from obstacles.

First, combining satellite image and the Voronoi field algorithm (VFA) generates rasterized environmental information and establishes navigation area boundary. Second, establishing a hazard function associated with navigation area boundary improves the evaluation function of the A^* algorithm and uses the improved A^* algorithm for global path planning. Finally, to reduce the number of redundant nodes in the planned path and smooth the path, node optimization and gradient descent method (GDM) are used. Then, a continuous smooth path that meets the actual navigation requirements of unmanned vehicle is obtained.

The simulation experiment proved that the proposed global path planning method can realize the control of the distance between the planned path and the obstacle by setting different navigation area boundaries. The node reduction rate is between 33.52% and 73.15%, and the smoothness meets the navigation requirements. This method is reasonable and effective in the global path planning process of unmanned vehicle and can provide reference to unmanned vehicles’ autonomous obstacle avoidance decision-making.

This study establishes navigation area boundary for the environment based on the VFA and uses the improved A* algorithm to generate a navigation path that takes into account both safety and economy. This study also proposes a method to solve the redundancy of grid environment path nodes and large-angle steering and to smooth the path to improve the applicability of the proposed global path planning method. The proposed global path planning method solves the requirements of path safety and smoothness.