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Interorganizational reciprocity plays a key role in relationships among software firms and open source communities. This study seeks to illuminate how a firm's open source strategy, characterized by its participation in the open source community, contributes to its financial performance.

Based on the norm of reciprocity and social capital theory, the study proposes a model comprising the behavioral antecedents and business results of a firm's symbiotic relationship with the open source community. Data were collected through a survey. Partial least squares-based structural equation modeling (PLS-SEM) was used to assess the results.

A firm's participative behaviors can have three dimensions: technology giving, technology taking and social participation. Technology taking directly impacts financial performance, whereas the effects of technology giving and social participation on financial performance are fully mediated by the firm's symbiotic relationship with the open source community.

Managers can understand how a specific behavior ultimately contributes to a symbiotic relationship or a firm's financial performance and how to flexibly align participation strategies with the business orientation.

The study adds to the open source literature by refining and enriching the conceptual domain of a firm's participative behaviors in open source communities. It also reveals how contrasting behavioral strategies impact a firm's financial performance.

The purpose of this study is to investigate wet multi-disc brake temperature field and optimal oil supply under continuous braking condition. The oil supply of wet multi-disc brake has a direct impact on the drivability and fuel economy for tracked vehicles. Too small flow will result in the higher temperature and failure of brake while excessive one will lead to slow engagement increasing disengaged torque and the transmission efficiency could decline notably. The optimal oil supply and brake temperature field were obtained in this research.

This article investigated on the heat dissipation capability and optimal oil supply of the brake by the means of CFX model. The working condition was continuous braking and the lubricating and cooling factors were included in the model.

That the complex trends with increased oil flow is inconsistent with the traditional formula in which the effects of grooves were neglected. The fitting curve of optimal oil supply can predict various needed oil flow in various rotating speed and it provides a theoretical guidance for oil supply design.

Traditional empirical formula of heat transfer coefficient and Reynolds equation solved by different methods could be difficult to deal with the complex boundary conditions of wet multi-disc brake. CFX model can solve the problem of complex boundary condition. The optimal oil supply curve can provide a theoretical guidance for oil supply design.

The main research problem is the relationship between the use motivation (UM) and use behavior (UB) of middle-aged and old short videos users and the difference of the influence of the use motivation of middle-aged and old users, a special group, on the usage behavior is analyzed.

By means of a questionnaire survey and in-depth interview, the middle-aged and old-aged users' short video use motivation and behavior and their influence relationship are discussed.

It is found that information appeal is the main motivation of middle-aged and old-aged users to use short videos and users with different social attributes have differences in motivation and there is a significant relationship between motivation and behavior.

The research objective is middle-aged and elderly short video users. And how to promote the transformation of middle-aged and old-aged users' use mentality and record and create their unique bright spots in the big stage of short videos with a more active and independent attitude, is of unique significance not only to the users themselves but also to the media content of this era and the users' existence in the technological change.

This paper aims to study the mechanism of hydrogen embrittlement in 12Cr2Mo1R(H) steel, which will help to provide valuable information for the subsequent hydrogen embrittlement research of this kind of steel, so as to optimize the processing technology and take more appropriate measures to prevent hydrogen damage.

The hydrogen diffusion coefficient of 12Cr2Mo1R(H) steel was measured by the hydrogen permeation technique of double electrolytic cells. Moreover, the influence of hydrogen traps in the material and experimental temperature on hydrogen diffusion behavior was discussed. The first-principles calculations based on density functional theory were used to study the occupancy of H atoms in the bcc-Fe cell, the diffusion path and the interaction with vacancy defects.

The results revealed that the logarithm of the hydrogen diffusion coefficient of the material has a linear relationship with the reciprocal of temperature and the activation energy of hydrogen atom diffusion in 12Cr2Mo1R(H) steel is 23.47 kJ/mol. H atoms stably exist in the nearly octahedral interstices in the crystal cell with vacancies. In addition, the solution of Cr/Mo alloy atom does not change the lowest energy path of H atom, but increases the diffusion activation energy of hydrogen atom, thus hindering the diffusion of hydrogen atom. Cr/Mo and vacancy have a synergistic effect on inhibiting the diffusion of H atoms in α-Fe.

This article combines experiments with first-principles calculations to explore the diffusion behavior of hydrogen in 12Cr2Mo1R(H) steel from the macroscopic and microscopic perspectives, which will help to establish a calculation model with complex defects in the future.

With excellent mechanic properties and hydrogen embrittlement (HE) resistance, 12Cr2Mo1R(H) steel is suitable to make hot-wall hydrogenation reactors. However, longtime exposure to a harsh environment of high-pressure hydrogen at medium temperature in practical application would still induce severe hydrogen uptake and eventually damage the mechanical properties of the steel. The study aims to evaluate the HE resistance of the steel under different tensile strain rates after hydrogen charging and analyze the hydrogen effect from atomic level.

This research studied the HE properties of 12Cr2Mo1R(H) steel by slow strain rate tests. Meanwhile, the effect of hydrogen on the structures and the mechanical properties of the simplified models of the steel was also investigated by first-principle calculations.

Experimental results showed that after hydrogen pre-charging in this work, hydrogen had little effect on the microstructure of the steel. The elongations and reduction of cross-sectional area of the samples reduced a lot, by contrast, the yield and tensile strengths changed slightly. The 12Cr2Mo1R(H) steel was not very susceptible to HE with a maximum embrittlement index of about 20.00%. First principles calculation results showed that after H dissolution, lattice distortion occurred and interstitial H atoms would preferentially occupy the tetrahedral interstitial site in bcc-Fe crystal and increase the stability of the supercells. With the increase of H atoms added into the simplified model, the steel still possessed a good ductility and toughness at a low hydrogen concentration, while the material would become brittle as the concentration of hydrogen continued to increase.

These finds can provide valuable information for subsequent HE studies on this steel.

Balancing accuracy and efficiency is an important evaluation index of response surface method. The purpose of this paper is to propose an adaptive order response surface method (AORSM) based on univariate decomposition model (UDM).

First, the nonlinearity of the univariate function can be judged by evaluating the goodness of fit and the error of curve fit rationally. Second, combining UDM with the order analysis of separate component polynomial, an easy-to-implement AORSM is proposed. Finally, several examples involving mathematical functions and structural engineering problems are studied in detail.

With the proposed AORSM, the orders of component functions in the original response surface can be determined adaptively and the results of those cases in this paper indicate that the proposed method performs good accuracy, efficiency and robustness.

Because just the cases with single failure mode and single MPP are studied in this paper, the application in multi-failure mode and multi-MPP cases need to be investigated in the coming work.

The nonlinearity of the univariate in the response surface can be determined adaptively and the undetermined coefficients of each component function are obtained separately, which reduces the computation dramatically.

“Sleeping beauties” are very common in science, so this paper aims to uncover the reasons and formulation mechanism of information awakening on a more general level. Based on this, the paper will further propose useful strategies to awaken those “sleeping beauties” earlier.

Explanation‐building of case study is used to develop some models of information awakening and also to uncover different types of reasons for triggering academic information to be awakened.

Based on the three basic elements of information utilisation, namely, information value, access channel and user needs, the paper summarises several reasons for information awakening: the information value is re‐mined because of the relevance among various information; different uses of information are discovered; information availability and visibility are improved; information is placed into the appropriate place; and, with time passing by, demands for the information rise.

The presence of excessive “sleeping beauties” is not only a kind of idleness and waste to knowledge, but also may result in aggravation of information redundancy and increasing cost of storage. The revelation of its essence and reasons is not only helpful to establish better management mechanism to awaken “sleeping beauties” and thus to maximise their value, but also helpful to distinguish “sleeping beauties” from “pseudo‐sleeping beauties” as early as possible, so that all that worthless information can be cleared up without hesitation.

Most existing studies remain on the level of collecting instances and interpreting specific cases, but this paper investigates reasons from a more general level. What is more, current understandings are very one‐sided in that they treat information awakening and delayed recognition as the same, so this paper clarifies their differentiation and summarises the reasons comprehensively.

By applying the American Customer Satisfaction Index (ACSI) model to virtual art exhibitions, this research aims to reveal insights into the factors impacting visitor satisfaction and electronic word-of-mouth (e-WOM). Furthermore, the investigation of exhibition promotion seeks to understand how external factors contribute to the overall visitor experience in virtual art exhibitions.

With advancements in virtual communication technology and the transformative impact of the COVID-19 pandemic in recent years, there has been a notable surge in the popularity of virtual art exhibitions based on the Internet. This study uses the ACSI model to examine visitor satisfaction and e-WOM in virtual art exhibitions. Additionally, it explores the influence of exhibition promotion on the ACSI model.

Key findings revealed that 1) both promotion efforts and e-WOM exhibited significant relationships with the ACSI model, and 2) most of the relationships within the ACSI model were consistent with previous research outcomes.

This study extends the ACSI model’s application to virtual art exhibitions, enhancing its relevance. Additionally, it addresses the knowledge gap concerning the direct impact of promotion on audience expectations and its relationship with the ACSI model in virtual art exhibitions. Furthermore, the research explores the influence of customer satisfaction on electronic word-of-mouth in exhibitions, offering valuable insights for exhibition evaluation systems. The study serves as a guide, providing data and models for researchers investigating virtual art exhibitions.

In recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A significant amount of research efforts has been thus dedicated to the automation of construction-related activities and visualization of the construction process. The purpose of this study is to investigate potential research opportunities in the integration of deep learning and XR technologies in construction engineering and management.

This study presents a literature review of 164 research articles published in Scopus from 2006 to 2021, based on strict data acquisition criteria. A mixed review method, consisting of a scientometric analysis and systematic review, is conducted in this study to identify research gaps and propose future research directions.

The proposed research directions can be categorized into four areas, including realism of training simulations; integration of visual and audio-based classification; automated hazard detection in head-mounted displays (HMDs); and context awareness in HMDs.

This study contributes to the body of knowledge by identifying the necessity of integrating deep learning and XR technologies in facilitating the construction engineering and management process.