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Despite the acknowledgment of the significant role leaders play in knowledge management, there has been limited focus on the dynamic relationship between one particular leader’s behavior and knowledge sharing of employees. This study aims to investigate the impact of leader generosity on employee knowledge sharing.

Drawing upon the generalized reciprocity theory, we develop a process model that examines the impact of leader generosity on knowledge sharing, and empirically tests the resulting mechanism. Based on event-contingent ESM that collected 1147 episodic data points, the data are analyzed by Mplus 8.30 and R software.

The findings indicate that employee gratitude and prosocial motivation respectively play a mediating role in the relationship between leader generosity and knowledge sharing. Additionally, leader generosity has an indirect impact on knowledge sharing via employee gratitude and prosocial motivation. Furthermore, relational self positively moderates the relationship between leader generosity and employee gratitude, while also moderates the chain mediation effect between leader generosity and knowledge sharing.

By exploring the important influence of leaders in implementing knowledge management practices, the authors demonstrate that a specific leader behavior (i.e. leader generosity) shapes the positive emotion and reciprocal motivation of employees and its subsequent impact on knowledge sharing. This paper complements the focus on knowledge sharing in the daily behavior literature of leaders, suggesting that leader generosity matters for employee knowledge sharing.

The purpose of this study is to improve the computational efficiency and accuracy of fatigue reliability analysis.

By absorbing the advantages of Markov chain and active Kriging model into the hierarchical collaborative strategy, an enhanced active Kriging-based hierarchical collaborative model (DCEAK) is proposed.

The analysis results show that the proposed DCEAK method holds high accuracy and efficiency in dealing with fatigue reliability analysis with high nonlinearity and small failure probability.

The effectiveness of the presented method in more complex reliability analysis problems (i.e. noisy problems, high-dimensional issues etc.) should be further validated.

The current efforts can provide a feasible way to analyze the reliability performance and identify the sensitive variables in aeroengine mechanisms.

To improve the computational efficiency and accuracy of fatigue reliability analysis, an enhanced active DCEAK is proposed and the corresponding fatigue reliability framework is established for the first time.

To provide valuable information for scholars to grasp the current situations, hotspots and future development trends of reliability analysis area.

In this paper, recent researches on efficient reliability analysis and applications in complex engineering structures like aeroengine rotor systems are reviewd.

The recent reliability analysis advances of engineering application in aeroengine rotor system are highlighted, it is worth pointing out that the surrogate model methods hold great efficiency and accuracy advantages in the complex reliability analysis of aeroengine rotor system, since its strong computing power can effectively reduce the analysis time consumption and accelerate the development procedures of aeroengine. Moreover, considering the multi-objective, multi-disciplinary, high-dimensionality and time-varying problems are the common problems in various complex engineering fields, the surrogate model methods and its developed methods also have broad application prospects in the future.

For the strong demand for efficient reliability design technique, this review paper may help to highlights the benefits of reliability analysis methods not only in academia but also in practical engineering application like aeroengine rotor system.

Seamless woven fashion is approachable via the Jacquard technology. With the rapid development of weaving technology and materials, an attempt is being made to expand and invent the technical and creative scopes of 3D Seamless Woven Fashion (SWF). The thrusts of the study are to establish complete design principles for advancing creation of SWF. In this study, three technical elements of weaving design have been identified in the course of SWF creation, i.e. elastic yarn, integrated structure, and integrated pattern. Past experiments so far suggested that it is possible to obtain different shrinkages as well as seamless woven textiles with varied richness and novel textures by adjusting the tightness of basic weaves. Moreover, three forms of layered structures, i.e., F (Flat), 3D-MnL (3-dimensional form on mono-layer) and 3D-MtL (3-dimensional appearance between multi-layers) were incorporated on different parts of a garment against specific requirements and/or performance. The construction of 3D shapes of SWF contributes to variety of fashions as well as woven textiles.

The purpose of this study is to explore a signal processing method to improve the angular rate accuracy of micro-electro-mechanical system (MEMS) gyroscope by combining numerous gyroscopes.

To improve the dynamic performance of the signal processing method, the interacting multiple model (IMM) can be applied to the fusion of gyroscope array. However, the standard IMM has constant Markov parameter, which may reduce the model switching speed. To overcome this problem, an adaptive IMM filter is developed based on the kurtosis of the gyroscope output, in which the transition probabilities are adjusted online by utilizing the dynamic information of the rate signal.

The experimental results indicate that the precision of the gyroscope array composed of six gyroscopes increases significantly and the kurtosis-based adaptive Markov parameter IMM filter (K-IMM) performs better than the baseline methods, especially under dynamic conditions. These experiments prove the validity of the proposed fusion method.

The proposed method can improve the accuracy of MEMS gyroscopes without breakthrough on hardware, which is necessary to extend their utility while not restricting the overwhelming advantages.

A K-IMM algorithm is proposed in this paper, which is used to improve the angular rate accuracy of MEMS gyroscope by combining numerous gyroscopes.

The purpose of this paper is to describe a novel universal error estimator and the adaptive time-stepping process in the generalized single-step single-solve (GS4-1) computational framework, applied for the fluid dynamics with illustrations to incompressible Navier–Stokes equations.

The proposed error estimator is universal and versatile that it works for the entire subsets of the GS4-1 framework, encompassing the nondissipative Crank–Nicolson method, the most dissipative backward differential formula and anything in between. It is new and novel that the cumbersome design work of error estimation for specific time integration algorithms can be avoided. Regarding the numerical implementation, the local error estimation has a compact representation that it is determined by the time derivative variables at four successive time levels and only involves vector operations, which is simple for numerical implementation. Additionally, the adaptive time-stepping is further illustrated by the proposed error estimator and is used to solve the benchmark problems of lid-driven cavity and flow past a cylinder.

The proposed computational procedure is capable of eliminating the nonphysical oscillations in GS4-1(1,1)/Crank–Nicolson method; being CPU-efficient in both dissipative and nondissipative schemes with better solution accuracy; and detecting the complex physics and hence selecting a suitable time step according to the user-defined error threshold.

To the best of the authors’ knowledge, for the first time, this study applies the general purpose GS4-1 family of time integration algorithms for transient simulations of incompressible Navier–Stokes equations in fluid dynamics with constant and adaptive time steps via a novel and universal error estimator. The proposed computational framework is simple for numerical implementation and the time step selection based on the proposed error estimation is efficient, benefiting to the computational expense for transient simulations.

The purpose of this paper is to develop a method for the existence, uniqueness and globally robust stability of the equilibrium point for Cohen–Grossberg neural networks with time-varying delays, continuous distributed delays and a kind of discontinuous activation functions.

Based on the Leray–Schauder alternative theorem and chain rule, by using a novel integral inequality dealing with monotone non-decreasing function, the authors obtain a delay-dependent sufficient condition with less conservativeness for robust stability of considered neural networks.

It turns out that the authors’ delay-dependent sufficient condition can be formed in terms of linear matrix inequalities conditions. Two examples show the effectiveness of the obtained results.

The novelty of the proposed approach lies in dealing with a new kind of discontinuous activation functions by using the Leray–Schauder alternative theorem, chain rule and a novel integral inequality on monotone non-decreasing function.

The purpose of this paper is to analyze long-term institutional causes and consequences of preference falsification by studying the evolution of China’s patriarchal clan system.

The historic study shows that although the clan system was abolished in the Qin dynasty, it re-emerged among high-standing families in the Han dynasty and spread to common people after the Tang dynasty.

The author submits that the clan system was an institutional response to the preference falsification problem that arose due to the dictatorial political institutions first established in the Qin dynasty. It helped people to take collective action by themselves and also opened a back door to influence government decisions. A piece of clear evidence is the co-evolution of the clan system and government personnel system.

In this sense, the clan system probably also helped to prolong the political institutions for 2,000 years.

This is the first institutional study on the clan system in China.

The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation methods of the system.

A multi-channel data acquisition scheme based on PCI-E (rapid interconnection of peripheral components) was proposed. The flexible biosensor is integrated with the flexible data acquisition card with monitoring capability, and the embedded (device that can operate independently) chip STM32F103VET6 is used to realize the simultaneous processing of multi-channel human health parameters. The human health parameters were transferred to the upper computer LabVIEW by intelligent clothing through USB or wireless Bluetooth to complete the transmission and processing of clinical data, which facilitates the analysis of medical data.

The smart clothing provides a mobile medical cloud platform for wearable medical through cloud computing, which can continuously monitor the body's wrist movement, body temperature and perspiration for 24 h. The result shows that each channel is completely accurate to the top computer display, which can meet the expected requirements, and the wearable instant care system can be applied to healthcare.

The smart clothing in this study is based on the monitoring and diagnosis of textiles, and the electronic communication devices can cooperate and interact to form a wearable textile system that provides medical monitoring and prevention services to individuals in the fastest and most accurate way. Each channel of the system is precisely matched to the display screen of the host computer and meets the expected requirements. As a real-time human health protection platform technology, continuous monitoring of human vital signs can complete the application of human motion detection, medical health monitoring and human–computer interaction. Ultimately, such an intelligent garment will become an integral part of our everyday clothing.

The purpose of this paper is to simulate the thermal performance of fluidic momentum controller (FMC) actuators in two case, with and without thermal distribution system on a three-axis configuration of FMC actuators to an orbital period of satellite. The results show the effectiveness of using a storage with FMC actuators.

One of the challenges during a satellite’s orbital mission is unpredictable external temperature perturbations. This system used as a collaborative thermal subsystem for microsatellite temperature passive control. The operating principles of the system are that each fluid rings are used in a microsatellite surface with pumps to stabilize the satellite. All fluid rings are connected to the satellite thermal distribution system (storage).

Simulation results show that with using of thermal distribution system, damping of satellite different surfaces temperature is rapidly possible to the event of thermal disturbances.

Numerical simulation is obtained by ANSYS Fluent software and pressure-velocity coupling is SIMPLE method and spatial discretization is second order accurate and first order in time, viscous model is k-e. In this regard, a solver algorithm is also developed.

In space research fields about FMC application as actuators to satellite system design, main goal is to research about role of this system to attitude and determination control system (ADCS) of satellites, and no study is performed on its role to satellite temperature damping. This study is exclusively simulated thermal distribution system (includes a storage and its connections) of a microsatellite equipped with FMC actuators. The idea of using a storage for FMC actuators is the innovative step of this research.