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This study investigated the mediating role of job satisfaction and the moderating role of career growth opportunity in the relationship between public service motivation (PSM) and public employees' turnover intention.

The authors recruited 587 public employees from Yunnan Province, China to test moderation and mediation hypotheses. The authors conducted confirmatory factor analysis to determine the discriminant and convergent validity of the measures of PSM, turnover intention, job satisfaction and career growth opportunity. Finally, the authors carried out bootstrapping to ascertain direct, indirect and conditional indirect effects.

PSM had a negative effect on public employees' turnover intention, but this relationship was partially mediated by job satisfaction. Career growth opportunity moderated the association between job satisfaction and turnover intention. In particular, the indirect effect of PSM on turnover intention through job satisfaction weakened under high career growth opportunities.

The results highlighted the significance of PSM and career growth opportunity in shaping public employees' work-related attitudes and behaviors. Public organizations should consider PSM a key criterion in recruitment and selection and pay more attention to the significance of intervening in career growth to satisfy public employees' psychological needs related to individual career development.

This study contributes to the literature on the disputed link between PSM and turnover intention and uncovered the underlying mechanism through which PSM affects public employees' turnover intention by proposing job satisfaction and career growth opportunity as a mediator and moderator, respectively.

In this paper, with the goal of reducing the fuel consumption of UAV, the engine performance optimization is studied and on the basis of aircraft/engine integrated control, the minimum fuel consumption optimization method of engine given thrust is proposed. In the case of keeping the given thrust of the engine unchanged, the main fuel flow of the engine without being connected to the afterburner is optimally controlled so as to minimize the fuel consumption.

In this study, the reference model real-time optimization control method is adopted. The engine reference model uses a nonlinear real-time mathematical model of a certain engine component method. The quasi-Newton method is adopted in the optimization algorithm. According to the optimization variable nozzle area, the turbine drop-pressure ratio corresponding to the optimized nozzle area is calculated, which is superimposed with the difference of the drop-pressure ratio of the conventional control plan and output to the conventional nozzle controller of the engine. The nozzle area is controlled by the conventional nozzle controller.

The engine real-time minimum fuel consumption optimization control method studied in this study can significantly reduce the engine fuel consumption rate under a given thrust. At the work point, this is a low-altitude large Mach work point, which is relatively close to the edge of the flight envelope. Before turning on the optimization controller, the fuel consumption is 0.8124 kg/s. After turning on the optimization controller, you can see that the fuel supply has decreased by about 4%. At this time, the speed of the high-pressure rotor is about 94% and the temperature after the turbine can remain stable all the time.

The optimal control method of minimum fuel consumption for the given thrust of UAV is proposed in this paper and the optimal control is carried out for the nozzle area of the engine. At the same time, a method is proposed to indirectly control the nozzle area by changing the turbine pressure ratio. The relevant UAV and its power plant designers and developers may consider the results of this study to reach a feasible solution to reduce the fuel consumption of UAV.

Fuel consumption optimization can save fuel consumption during aircraft cruising, increase the economy of commercial aircraft and improve the combat radius of military aircraft. With the increasingly wide application of UAVs in military and civilian fields, the demand for energy-saving and emission reduction will promote the UAV industry to improve the awareness of environmental protection and reduce the cost of UAV use and operation.

Current healthcare applications produce a complex and inaccessible set of data that often needs to be investigated simultaneously. As such the conflicting software applications and mental effort being demanded from the user result in time‐consuming analysis and diagnosis. The purpose of this paper is to provide a prototype, interactive system for management of multiple data sets, currently used for gait analysis capturing, reconstruction and diagnosis. In summary, this work is concerned with the development of interactive information‐visualisation software that assists medical practitioners in simplifying and enhancing the retrieval, visualisation and analysis of medical data with the intention of improving the overall system leading to an improved service for the user and patient experience.

The design of the proposed system aims to combine all the related existing software currently used for gait analysis and diagnosis under one, user‐friendly package. The latter will have the capacity to offer also real‐time, three dimensional (3D) representations of all the derived data (CT, MRI, motion capture) in an interactive virtual reality (VR) environment.

It is intended that the proposed prototype solutions will enhance interactive systems for management of multiple data sets, currently used for gait analysis capturing, reconstruction and diagnosis. The derived data encapsulate a plethora of multimedia information aiming to enhance medical visualisation.

The proposed system offers simulation capacity and a VR visualisation experience, which enhances the gait analysis diagnostic process. The 3D data can be manipulated in real‐time through a novel human‐computer interface which uses multimodal interaction through the use of graphical user interfaces and gesture recognition. The system aims towards a cost‐effective, clearly presented and timely accessible system that follows a threefold approach; It entails managing the extensive amount of the daily produced medical data, combining the scattered information related to one patient in one interface with a filtering criteria to the required information, and visualising in 3D the data from different sources, in order to improve 3D mental mapping, increase productivity and consequently ameliorate quality of service and management.

The paper aims to explore the factors that influence the risk perception. The moderating roles of purchase experience and purchase involvement are also investigated.

The conceptual model is framed into the SOR (stimulus-organism-response) model, which was tested using data collected from the users of a leading group buying platform in China, with the help of LISREL.

The result indicates that both vendor- and intermediary-related factors exert negative yet significant influences on perceived risk. The relationships between vendor-related attributes and perceived risk are contingent on purchase involvement. The relationships between intermediary-related attributes and perceived risk are subject to purchase experience.

This study explores the moderating effects of purchase experience and purchase involvement based on the characteristics of group buying, demonstrating the differences from traditional online shopping.

Basic safety message (BSM) is a core subset of standard protocols for connected vehicle system to transmit related safety information via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). Although some safety prototypes of connected vehicle have been proposed with effective strategies, few of them are fully evaluated in terms of the significance of BSM messages on performance of safety applications when in emergency.

To address this problem, a data fusion method is proposed to capture the vehicle crash risk by extracting critical information from raw BSMs data, such as driver volition, vehicle speed, hard accelerations and braking. Thereafter, a classification model based on information-entropy and variable precision rough set (VPRS) is used for assessing the instantaneous driving safety by fusing the BSMs data from field test, and predicting the vehicle crash risk level with the driver emergency maneuvers in the next short term.

The findings and implications are discussed for developing an improved warning and driving assistant system by using BSMs messages.

The findings of this study are relevant to incorporation of alerts, warnings and control assists in V2V applications of connected vehicles. Such applications can help drivers identify situations where surrounding drivers are volatile, and they may avoid dangers by taking defensive actions.

The purpose of this paper is to design a unified operational design domain (ODD) monitoring framework for mitigating Safety of the Intended Functionality (SOTIF) risks triggered by vehicles exceeding ODD boundaries in complex traffic scenarios.

A unified model of ODD monitoring is constructed, which consists of three modules: weather condition monitoring for unusual weather conditions, such as rain, snow and fog; vehicle behavior monitoring for abnormal vehicle behavior, such as traffic rule violations; and road condition monitoring for abnormal road conditions, such as road defects, unexpected obstacles and slippery roads. Additionally, the applications of the proposed unified ODD monitoring framework are demonstrated. The practicability and effectiveness of the proposed unified ODD monitoring framework for mitigating SOTIF risk are verified in the applications.

First, the application of weather condition monitoring demonstrates that the autonomous vehicle can make a safe decision based on the performance degradation of Lidar on rainy days using the proposed monitoring framework. Second, the application of vehicle behavior monitoring demonstrates that the autonomous vehicle can properly adhere to traffic rules using the proposed monitoring framework. Third, the application of road condition monitoring demonstrates that the proposed unified ODD monitoring framework enables the ego vehicle to successfully monitor and avoid road defects.

The value of this paper is that the proposed unified ODD monitoring framework establishes a new foundation for monitoring and mitigating SOTIF risks in complex traffic environments.

The purpose of this paper is to investigate the explosive performance and explosion damage mechanism of T-beam bridge structure.

On the basis of the existing specification, two T-beam bridge models were designed and fabricated. Test specimens of different explosive dosage and different blast height were carried out. The mechanical process, failure mode, blast damage model, damage identification mechanism and blast evolution law and quantitative evaluation were taken into account.

The results revealed that the web plate fracture failure is the key to the unstable failure of the whole T-beam bridge. The explosion failure phenomenon and blast damage evaluation criterion of RC T-beam bridge was divided into five stages: the original cracks stage of concrete material (D = 0 ∼ 0.1), the fractures initiation stage of concrete material (D = 0.1 ∼ 0.3), the stable expansion stage of cracks in concrete material (D = 0.3 ∼ 0.55), the unstable expansion stage of cracks in concrete material (D = 0.55 ∼ 0.8), the explosion fracture of steel bars and the overall instability and damage of the bridge (D = 0.8 ∼ 1.0), which can also be described as basically intact, slight damage, moderate damage, severe damage and collapsed.

The research result will provide basis for the antiknock evaluation and damage repair technical specifications of the RC T-beam bridge.

The research results of damage evaluation serve as a basis for damage repair and reinforcement of bridge structures after explosion.

This paper aims to disentangle the mechanism linking digital servitization and manufacturing firm performance. The contributions of the service networks and slack resources are analyzed.

Drawing on a survey of manufacturing firms that have implemented or are implementing digital service projects in China, this paper examines the mediation effect of service networks and the moderated mediation effect of slack resources to capture the role of service networks and slack resources in the relationship between digital servitization and manufacturing firm performance.

Both basic and advanced digital services can equally contribute to manufacturing firm performance. Service networks mediate the relationship between basic digital servitization and manufacturing firm performance. No moderated mediation effect of slack resources is found, but slack resources negatively moderate the effects of basic digital services on service networks and positively impact service networks.

The mediating mechanism of service networks in the relationship between digital servitization and manufacturing firm performance is theorized, and it is clarified that service networks mediate the association between basic digital services and manufacturing firm performance but not advanced digital services. Additionally, there is no significant difference in performance implications when manufacturing firms provide basic versus advanced digital services, answering the call for research on the various types of digital servitization. This paper also identifies firms’ slack resources as the boundary conditions under which basic digital services influence service networks and the positive impacts of slack resources on service networks, bridging the network literature, organizational slack literature and digitalization literature under the framework of service ecosystem research.

The purpose of this paper is to propose a new strong-form numerical method, called the free element method, for solving general boundary value problems governed by partial differential equations. The main idea of the method is to use a locally formed element for each point to set up the system of equations. The proposed method is used to solve the fluid mechanics problems.

The proposed free element method adopts the isoparametric elements as used in the finite element method (FEM) to represent the variation of coordinates and physical variables and collocates equations node-by-node based on the newly derived element differential formulations by the authors. The distinct feature of the method is that only one independently formed individual element is used at each point. The final system of equations is directly formed by collocating the governing equations at internal points and the boundary conditions at boundary points. The method can effectively capture phenomena of sharply jumped variables and discontinuities (e.g. the shock waves).

a) A new numerical method called the FEM is proposed; b) the proposed method is used to solve the compressible fluid mechanics problems for the first time, in which the shock wave can be naturally captured; and c) the method can directly set up the system of equations from the governing equations.

This paper presents a completely new numerical method for solving compressible fluid mechanics problems, which has not been submitted anywhere else for publication.

This paper aims to improve the performance of the autonomous optical navigation using relativistic perturbation of starlight, which is a promising technique for future space missions. Through measuring the change in inter-star angle due to the stellar aberration and the gravitational deflection of light with space-based optical instruments, the position and velocity vectors of the spacecraft can be estimated iteratively.

To enhance the navigation performance, an integrated optical navigation (ION) method based on the fusion of both the inter-star angle and the inter-satellite line-of-sight measurements is presented. A Q-learning extended Kalman filter (QLEKF) is designed to optimize the state estimate.

Simulations illustrate that the integrated optical navigation outperforms the existing method using only inter-star angle measurement. Moreover, the QLEKF is superior to the traditional extended Kalman filter in navigation accuracy.

A novel ION method is presented, and an effective QLEKF algorithm is designed for information fusion.