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The purpose of this paper is to introduce a new method for the design of a pressure sensor in the hyperbaric environment.

The new method focuses on two vital parameters that are closely related to the output and sensitivity of the sensor. The rectangular diaphragm structure is adopted, and the piezoresistors are planted on the surface accordingly. To verify the effect of the method, a contrastive sensor chip is fabricated in a conventional way, and two types of sensor chips are tested at the same time.

The new method for the design of a pressure sensor is advisable and favorable. The sensor fabricated by the method possesses outstanding high sensitivity and a wide measurement range.

This paper provides a new idea for increasing the measurement range of the pressure sensor with an acceptable sacrifice of sensitivity.

In this paper, microbial transglutaminase (MTG) was applied to process silk fabric for improving its crease resistance under the prerequisite of maintaining other performances. Not only was the effect of MTG on silk fabric investigated through the Fourier transform infrared spectroscopy (FR), but analysis was also undertaken in the microcosmic structure of fibroin through the scanning electron microscope (SEM). Solo MTG treatment as well as compound treatments of MTG followed by hydrogen peroxide, protease and ultrasonic, all showed that MTG can improve the crease resistance of silk fabric. It also enhanced its tensile breaking strength or amended damage in the tensile breaking strength caused by pretreatments.

Simultaneously, comparison with other treatments showed that compound treatment of MTG followed by ultrasonic exerted a better coordinated effect and conferred better performances, which made the wrinkle recovery angle (WRA) increase by 17.4% and tensile breaking strength improve by 11.2% respectively. At the same time, other performances were still maintained well.

The authors present a fist attempt to test the mediating role of humor in the relation between unruly passenger behavior and occupational stress in cabin crews.

This study used an experience sampling design to investigate the relationship between a frequent job hassle in air service provision, namely unruly passenger behavior (UPB), and the stress experienced by flight attendants.

The results of multilevel analyses show that UPB is positively related to the use of aggressive humor and negatively related to the use of affiliative humor in cabin crews. Moreover, humor mediates the relationship between unruly passenger behavior and stress. In addition the results show that general self-efficacy as a personal resource buffers the association between passenger misconduct and the use of aggressive humor.

This study is among the first empirical attempts to explore the role of humor as a mediator between uncivil customer behavior and stress in air service employee.

This paper seeks to build a mathematical model to deduct the twists distribution in the slub‐yarn.

The model, considering the shearing modulus and polar moment of inertia of the yarn, influenced by the yarn density, is established based on the bar torsion model. The twists distribution in the slub‐yarn is concluded based on the analysis of the results. The rules were verified via an indirect method, by testing the breaking strength of the slub‐yarn.

The results of the analysis showed that twists in every section of the slub‐yarn are in inverse proportion to the square of the line density of the corresponding section. Slub length is a key factor to the twist in the base yarn, and the increase of the slub length will increase the twist; while the multiple is the key factor to the slub twist, and the enhancement of the multiple will decrease the twist significantly.

The analysis cannot be verified via a direct method. A new, more conceivable direct method should be utilized to test the result.

The paper builds a base for the research of the mechanical properties of slub‐yarn and gives directions to the slub‐yarn production.

The purpose of this study is to investigate the mechanism of shared leadership on team members’ innovative behavior.

Paired questionnaires were collected from 89 scientific research teams in the Beijing-Tianjin-Hebei region of China at two-time points with a time lag of 4 months. Then multilevel structural equation model method was applied to analyze the multiple mediating effects.

This study finds that: the form of shared leadership in scientific research teams of universities; shared leadership has a positive impact on team members’ innovative behavior; there are multiple mediations in the relationship including synchronization and sequence of creative self-efficacy and achievement motivation.

According to the “stimulus-organism-response” model, this paper has constructed a multi-level theoretical model that shared leadership influences individual innovation behavior and reveals the “black box” from the perspective of psychological mechanism. It not only verifies that “can-do” shapes “willing to do” but also makes up for the gap of an empirical test of the effectiveness of shared leadership in scientific research teams of universities. Besides, the formal scale of shared leadership in the Chinese situation is revised, which can provide a reference for future empirical research on shared leadership. The research conclusions provide new ideas for improving the management of scientific research teams in universities.

This paper aims to investigate the mechanism of Ni particles distribution in the liquid Sn3.5Ag melt under the external static magnetic field. The control steps of Ni particles and the Sn3.5Ag melt metallurgical process were studied. After aging, the microhardness of pure Sn3.5Ag, Sn3.5Ag containing randomly distributed Ni particles and Sn3.5Ag containing columnar Ni particles were compared.

Place the sample in a crucible for heating. After the sample melts, place a magnet directly above and below the sample to provide a magnetic field. Sn3.5Ag with the different morphological distribution of Ni particles was obtained by holding for different times under different magnetic field intensities. Finally, pure Sn3.5Ag, Sn3.5Ag with random distributed Ni particles and Sn3.5Ag with columnar Ni particles were aged and their microhardness was tested after aging.

The experimental results show that with the increase of magnetic field strength, the time for Ni particle distribution in Sn3.5Ag melt to reach equilibrium is shortened. After aging, the microhardness of Sn3.5Ag containing columnar nickel particles is higher than that of pure Sn3.5Ag and Sn3.5Ag containing randomly distributed nickel particles. A chemical reaction is the control step in the metallurgical process of nickel particles and molten Sn3.5Ag.

Under the action of the magnetic field, Ni particles in Sn3.5Ag melt will be arranged into columns. With the increase of magnetic field strength, the shorter the time for Ni particles in Sn3.5Ag melt to arrange in a column. With the extension of the service time of the solder joint, if Sn3.5Ag with columnar nickel particles is used as the solder joint material, its microhardness is better than Sn3.5Ag with arbitrarily distributed nickel particles and pure Sn3.5Ag.

This paper aims to obtain optimal specialization mode and level for complex network or system structures. In the e-commerce system, this paper studies the changes of each transaction subject in the process of ecological structure based on the income level of each transaction subject.

This paper aims to research the change of transaction efficiency evolution process of intermediaries. With the improvement of transaction efficiency, intermediaries interact with other transaction subjects at given modes in e-commerce systems. This paper analyzes the relationship between the factors of production and trade and explains the quantitative relationship between them in the form of mathematical modeling. An evolution simulation framework is established to elaborate the simulation process and method of crowd network in e-commerce ecosystem and then sets up the simulation experiment.

During simulation processes, the changes of data are observed and analyzed to obtain the optimal evolution paths and specialization modes. Furthermore, this paper provides solid supports for the research of the quantitative analysis of ecological structure evolutions.

Evolution simulation of ecological structure is first proposed in the topic of crowd network. It is with the aid of the concept of ecology, the theory and method, simulation of complex network structure and system structure. This paper analyses and researches the evolution process of optimal specialization modes and intelligent level of crowd networks with transaction efficiency changing. The ecological structure optimal evolution paths can be obtained by trend of simulations.

Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations.

After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations).

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).

Inspired by the development of eco-friendly flexible electronics, this paper aims to present a series of paper-based electronics drawn by pencils, which can be used as favorable sensing elements in daily life.

Pencil traces are deposited on the porous surface of Xerox paper by the mechanical exfoliation during writing process, which can be used as basic components to construct functional electronics for daily sensing applications. By changing pencil grade, the obtained traces can work as conductive wires, electrodes, resistors and piezoresistive gauges.

The experimental results confirm their practical applications in sensing several daily activities, including finger motion, touching and the temperature of water in paper cup. Moreover, the used electronics can be easily handled and recycled.

The shortage in functionality, reliability and performance consistency induced by manual operation is an evident challenge, which makes the pencil-on-paper devices more suitable to work as a temporary solution to satisfying the demands from emergency circumstances.

The pencil-on-paper devices, motivated by the electroconductibility and piezoresistivity of pencil trace, can be explored as sensing prototypes in detecting daily activities. Meantime, their advances in easy accessibility, rapid fabrication, low cost and eco-fitness endow them excellent capacity of meeting the “on-site, real-time” demands.

Over the past decades, there has been significant research effort dedicated to the development of autonomous vehicles. The decision-making system, which is responsible for driving safety, is one of the most important technologies for autonomous vehicles. The purpose of this study is the use of an intensive learning method combined with car-following data by a driving simulator to obtain an explanatory learning following algorithm and establish an anthropomorphic car-following model.

This paper proposed car-following method based on reinforcement learning for autonomous vehicles decision-making. An approximator is used to approximate the value function by determining state space, action space and state transition relationship. A gradient descent method is used to solve the parameter.

The effect of car-following on certain driving styles is initially achieved through the simulation of step conditions. The effect of car-following initially proves that the reinforcement learning system is more adaptive to car following and that it has certain explanatory and stability based on the explicit calculation of R.

The simulation results show that the car-following method based on reinforcement learning for autonomous vehicle decision-making realizes reliable car-following decision-making and has the advantages of simple sample, small amount of data, simple algorithm and good robustness.