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This study aims to understand the epistemic foundation of the classification applied in the first Chinese library catalogue, the Seven Epitomes (Qilue).

Originating from a theoretical stance that situates knowledge organization in its social context, the study applies a multifaceted framework pertaining to five categories of textual data: the Seven Epitomes; biographical information about the classificationist Liu Xin; and the relevant intellectual, political, and technological history.

The study discovers seven principles contributing to the epistemic foundation of the catalogue's classification: the Han imperial library collection imposed as the literary warrant; government functions considered for structuring texts; classicist morality determining the main classificatory structure; knowledge perceived and organized as a unity; objects, rather than subjects, of concern affecting categories at the main class level; correlative thinking connecting all text categories to a supreme knowledge embodied by the Six Classics; and classicist moral values resulting in both vertical and horizontal hierarchies among categories as well as texts.

A major limitation of the study is its focus on the main classes, with limited attention to subclasses. Future research can extend the analysis to examine subclasses of the same scheme. Findings from these studies may lead to a comparison between the epistemic approach in the target classification and the analytic one common in today's bibliographic classification.

The study is the first to examine in depth the epistemic foundation of traditional Chinese bibliographic classification, anchoring the classification in its appropriate social and historical context.

Counterproductive work behavior (CWB) has grown into a significant problem in the tourism industry, for both individual employees and organizations. Employees who feel ostracized in their workplace often engage in negative and disruptive behaviors. The purpose of this study is to explore the psychological mechanism between workplace ostracism and CWB among tourism employees.

Drawing on psychological contract theory and social cognitive theory, the study proposed a research framework to explain tourism employees’ counterproductive behavior. Data were collected from 228 hotel employees at two time points in Huangshan, China. Hierarchical regression and SPSS-PROCESS Macro were used to test all the hypotheses.

Findings show that workplace ostracism significantly increases employee CWB, mediated by psychological contract violation. Workplace ostracism increases perceptions of psychological contract violation when employee self-esteem is higher. The mediating effect of psychological contract violation is also moderated by self-esteem.

Using the framework of psychological contract theory and social cognitive theory, the authors advance the organizational behavior literature in the tourism field. The authors contextualize the uniqueness of Chinese workplace behavior and highlight the need to understand “losing face (mianzi) view” in workplace relationships. This research contributes to better understanding the dark side of tourism workplace behavior by examining the effects of psychological contract violation and employee’s self-esteem on workplace ostracism and CWB.

旅游业中的反生产行为（CWB）已经成为一个重要问题, 反生产行为对员工和组织都会产生影响。在工作场所感到被排斥的员工往往会从事消极和破坏性的行为。本文的目的是研究旅游业员工工作场所排斥与反生产行为之间的心理机制。

基于心理契约理论和社会认知理论, 本研究提出了一个研究框架来解释旅游业员工的反生产行为发生机制。我们在中国黄山景区对228名酒店员工进行了两个时间点的问卷调查。采用分层回归和SPSS PROCESS Macro来测试所有假设。

结果表明 工作场所排斥显著增加员工反生产行为, 心理契约违背在其中起着中介作用。当员工自尊心较高时, 职场排斥对心理契约违反的感知影响更强。心理契约违背的中介效应也受到自尊心的调节。

我们运用心理契约理论和社会认知理论的框架, 推动了旅游领域的组织行为研究进展。我们讨论了中国情境下职场行为的独特性, 并强调在职场关系中需要考虑“面子观”。我们通过展示心理契约违背和员工自尊心对工作场所排斥和反生产行为（CWB）的影响, 有助于更好地理解旅游工作场所行为的负面影响。

El comportamiento laboral contraproducente (CLC) en la industria turística se ha convertido en un problema significativo tanto para los empleados individuales como para las organizaciones. Los empleados que se sienten marginados en su lugar de trabajo suelen participar en comportamientos negativos y disruptivos. El objetivo de este trabajo es examinar los efectos de la violación del contrato psicológico y la autoestima del empleado en el ostracismo en el lugar de trabajo y en el comportamiento laboral contraproducente CLC y agregar nuevos conocimientos para comprender mejor el lado oscuro del comportamiento laboral turístico.

Realizamos una encuesta de cuestionario a 228 empleados de hotel en dos momentos en Huangshan, China. Se utilizaron la regresión jerárquica y el SPSS PROCESS Macro para probar todas las hipótesis.

Los resultados muestran que 1) el ostracismo en el lugar de trabajo aumenta significativamente la CLC de los empleados. 2) La violación psicológica del contrato juega un papel mediador entre el ostracismo en el lugar de trabajo y CLC. 3) El ostracismo en el lugar de trabajo aumenta las percepciones de violación psicológica del contrato cuando la autoestima de los empleados es mayor. 4) El efecto mediador de la violación psicológica del contrato también es moderado por la autoestima.

Utilizando el marco de la teoría del contrato psicológico y la teoría cognitiva social, avanzamos en la literatura del comportamiento organizacional en el campo del turismo. Contextualizamos la singularidad del comportamiento en el lugar de trabajo chino y destacamos la necesidad de comprender la 'pérdida de la visión de la cara (mianzi)' en las relaciones laborales. Esta investigación contribuye con nuevos conocimientos para comprender mejor el lado oscuro del comportamiento turístico en el lugar de trabajo al examinar los efectos de la violación psicológica del contrato y la autoestima de los empleados en el ostracismo en el lugar de trabajo.

Recently, digital competence has become one of the most important work competencies of employees. This study investigated students' digital competence in the context of Chinese higher education and examined digital competence's relationship with students' career adaptability.

The participants were 298 Chinese higher education students from both universities and colleges. MANOVA (Multivariate Analysis of Variance) was carried out through SPSS (Statistical Package for the Social Sciences) 26.0 to examine whether digital competence varied with the students' personal characteristics, i.e. gender, grade level and school type. In addition, the structural equation model was employed with Mplus 8.3 to analyse the relationship between digital competence and career adaptability as well as the mediation role of digital informal learning and academic performance.

The descriptive statistics revealed that students performed best in the safety construct, whilst worst in the digital content creation construct. The result of MANOVA showed that the digital competence of the participants significantly varied with participants' gender, school type and grade level. Furthermore, the structural equation model results demonstrated that higher education students' digital competence was positively associated with the students' career adaptability. And the mediation role of digital informal learning and academic performance was also confirmed.

To the authors' knowledge, this is the first study focussing on the relationship between digital competence and career adaptability. In particular, both working and learning perspectives were considered to explore this relationship. Besides, the authors also displayed Chinese higher education students' digital competence with consideration of different districts and school types.

With the continuous development of aerospace technology, space exploration missions have been increasing year by year, and higher requirements have been placed on the upper level rocket. The purpose of this paper is to improve the ability to identify and detect potential targets for upper level rocket.

Aiming at the upper-level recognition of space satellites and core components, this paper proposes a deep learning-based spatial multi-target recognition method, which can simultaneously recognize space satellites and core components. First, the implementation framework of spatial multi-target recognition is given. Second, by comparing and analyzing convolutional neural networks, a convolutional neural network model based on YOLOv3 is designed. Finally, seven satellite scale models are constructed based on systems tool kit (STK) and Solidworks. Multi targets, such as nozzle, star sensor, solar,etc., are selected as the recognition objects.

By labeling, training and testing the image data set, the accuracy of the proposed method for spatial multi-target recognition is 90.17%, which is improved compared with the recognition accuracy and rate based on the YOLOv1 model, thereby effectively verifying the correctness of the proposed method.

This paper only recognizes space multi-targets under ideal simulation conditions, but has not fully considered the space multi-target recognition under the more complex space lighting environment, nutation, precession, roll and other motion laws. In the later period, training and detection can be performed by simulating more realistic space lighting environment images or multi-target images taken by upper-level rocket to further verify the feasibility of multi-target recognition algorithms in complex space environments.

The research in this paper validates that the deep learning-based algorithm to recognize multiple targets in the space environment is feasible in terms of accuracy and rate.

The paper helps to set up an image data set containing six satellite models in STK and one digital satellite model that simulates spatial illumination changes and spins in Solidworks, and use the characteristics of spatial targets (such as rectangles, circles and lines) to provide prior values to the network convolutional layer.

Non-fossil fuels are receiving increasing attention within the context of addressing global climate challenges. Based on a review of non-fossil fuel consumption in major countries worldwide from 1985 to 2015, the purpose of this paper is to analyze trends for global non-fossil fuel consumption, share of fuel consumption and inequality.

The similarities were obtained between the logarithmic mean divisia index and the mean-rate-of-change index decomposition analysis methods, and a method was proposed for complete decomposition of the incremental Gini coefficient.

Empirical analysis showed that: global non-fossil fuel consumption accounts for a small share of the total energy consumption, but presents an increasing trend; the level of global non-fossil fuel consumption inequality is high but has gradually declined, which is mainly attributed to the concentration effect; inequality in global non-fossil fuel consumption is mainly due to the difference between nuclear power and hydropower consumption, but the contributions of nuclear power and hydropower to per capita non-fossil fuel consumption are declining; and population has the greatest influence on global non-fossil fuel consumption during the sampling period.

The main contribution of this study is its analysis of global non-fossil fuel consumption trends, disparities and driving factors. In addition, a general formula for complete index decomposition is proposed and the incremental Gini coefficient is wholly decomposed.

The purpose of this study is to find out how electronic word of mouth (eWOM) may affect evaluations of products with different brand images. In particular, the study explores differential eWOM impacts across several brand types and extension categories.

An experiment with 2 (brand image: prestige/function) × 2 (category similarity: low/high) × 2 (eWOM message type: positive/negative) between-subjects design was used to examine the impacts of eWOM on different types of brand extensions. A total of 268 subjects from a public university in the Southwest participated in the study. Analysis of Variance (ANOVA) was used in analyzing the data.

The findings highlight the differential impact of eWOM on brand extension evaluations with different brand images. First, eWOM is more effective in influencing evaluations of functional brand extensions than prestige brand extensions. Second, whereas negative eWOM does equally bad on both high- and low-similarity brand extensions, positive eWOM is more effective in improving evaluations of high-similarity extensions than low-similarity extensions.

This study is the first to examine the impact of eWOM on products with different brand images. This is a critical issue for brand managers who allocate limited marketing resources to monitoring and managing vast amounts of eWOM activities. The findings provide important guidance for managing social media marketing communications.

The purpose of this paper is to improve the efficiency of on-orbit operations through the top-level task design based on DoDAF. Based on the existing upper stage rocket technology, orbit transfer vehicles (OTVs) have developed rapidly in recent years. However, the lack of decision guidance based on overall task analysis requires integrating top-level analysis and bottom-level execution to achieve the smooth development of full-process tasks.

Using the Department of Defense Architecture Framework (DoDAF) as a reference, this paper performs the top-level mission analysis modeling of the on-orbit rendezvous and capture of the OTV. Moreover, the typical operational view products are obtained, and the cooperative relations among the mission requirements, the system requirements, and the functional requirements are also analyzed.

The results show that the attitude of the OTV changes violently during the maneuver and rendezvous phases. In addition, the view products can be optimized based on the results.

The proposed DoDAF-based on-orbit task integration analysis method achieves the effective fusion of high-level analysis and bottom-level execution of OTV on-orbit rendezvous and capture task through the top-level task modeling, operation view generation and task relationship analysis. According to the requirements and constraints of the on-orbit rendezvous and capture task, the control instructions of the vehicle are efficiently generated under the DoDAF framework.

The purpose of this paper is to analyze lubrication characteristics of a tilting pad thrust bearing considering the effect of the thermal elastic deformation of the pad and collar.

This study used the fluid–solid interaction (FSI) technique to investigate the lubrication characteristics of a tilting pad thrust bearing for several typical operating conditions. The influences of the rotational speed, the thrust load and the oil supply temperature on the lubrication characteristics were analyzed.

The three-dimensional (3D) film model clearly shows that there is no pressure gradient but large temperature gradients across the film thickness. The wall heat transfer coefficients on the pad surfaces distribute in a very complex way and change within a large range. The rotational speed, the thrust load and the oil supply temperature have great but different influences on the lubrication characteristics.

This paper has preliminarily revealed the lubrication mechanism of the tilting-pad thrust bearings. The 3D FSI method is suggested to evaluate the thermal-elastic-hydrodynamic deformations of thrust bearings instead of the conventional method which iteratively solves the Reynolds equation, the energy equation, the heat conduction equation and the elastic equilibrium equation. Using FSI method, the heat transfer coefficients on the pad surfaces can be evaluated better.

This study aims to propose a series of numerical and surrogate models to investigate the aerodynamic pressure inside cracks in high-speed railway tunnel linings and to predict the stress intensity factors (SIFs) at the crack tip.

A computational fluid dynamics (CFD) model is used to calculate the aerodynamic pressure exerted on two cracked surfaces. The simulation uses the viscous unsteady κ-ε turbulence model. Using this CFD model, the spatial and temporal distribution of aerodynamic pressure inside longitudinal, oblique and circumferential cracks are analyzed. The mechanism behind the pressure variation in tunnel lining cracks is revealed by the air density field. Furthermore, a response surface model (RSM) is proposed to predict the maximum SIF at the crack tip of circumferential cracks and analyze its influential parameters.

The initial compression wave amplifies and oscillates in cracks in tunnel linings, resulting from an increase in air density at the crack front. The maximum pressure in the circumferential crack is 2.27 and 1.76 times higher than that in the longitudinal and oblique cracks, respectively. The RSM accurately predicts the SIF at the crack tip of circumferential cracks. The SIF at the crack tip is most affected by variations in train velocities, followed by the depth and length of the cracks.

The mechanism behind the variation of aerodynamic pressure in tunnel lining cracks is revealed. In addition, a reliable surrogate model is proposed to predict the mechanical response of the crack tip under aerodynamic pressures.