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This study aims to overcome the problem of traditional association rules relying almost entirely on expert experience to set relevant interest indexes in mining. Second, this project can effectively solve the problem of four types of rules being present in the database at the same time. The traditional association algorithm can only mine one or two types of rules and cannot fully explore the database knowledge in the decision-making process for library recommendation.

The authors proposed a Markov logic network method to reconstruct association rule-mining tasks for library recommendation and compared the method proposed in this paper to traditional Apriori, FP-Growth, Inverse, Sporadic and UserBasedCF algorithms on two history library data sets and the Chess and Accident data sets.

The method used in this project had two major advantages. First, the authors were able to mine four types of rules in an integrated manner without having to set interest measures. In addition, because it represents the relevance of mining in the network, decision-makers can use network visualization tools to fully understand the results of mining in library recommendation and data sets from other fields.

The time cost of the project is still high for large data sets. The authors will solve this problem by mapping books, items, or attributes to higher granularity to reduce the computational complexity in the future.

The authors believed that knowledge of complex real-world problems can be well captured from a network perspective. This study can help researchers to avoid setting interest metrics and to comprehensively extract frequent, rare, positive, and negative rules in an integrated manner.

The purpose of this study is to investigate the effect of engineered micro-structures on the tribological properties of metal-polyetheretherketone (PEEK) surface.

Circular dimples with diameters of 25 and 50 µm were designed and manufactured on PEEK plate specimens using picosecond laser. Reciprocating friction and wear tests on a ball-on-flat configuration were performed to evaluate the tribological properties of the designed micro-structures in dry contacts. The loading forces of 0.9 and 3 N were applied.

As a result, obvious fluctuations of coefficient of friction curve were observed in tribosystems consisting of non-textured and textured PEEK with circular dimples of 25 µm in diameter. GCr15 ball/textured PEEK plate specimens with circular dimples of 50 µm in diameter revealed a superior friction and wear property.

Different to the existing studies in which the tribopairs consist of hard bearing couples, this study investigated the tribological properties of the engineered micro-structures on the hard-on-soft bearing couples.

This study aims to solve the premature failure of the rubber stator due to wear, reduce the frictional resistance moment of the screw pump to solve the problem of a model of Daqing oilfield screw pump oil recovery system shutdown after the difficult start.

For the first time, the rotor surface of a screw pump was treated with dot-matrix texture to study the effect of dot matrix texture on the tribological performance of the stator-rotor friction subsets of screw pump. Reciprocating friction tests with different texture morphologies (S-shape, double tongue) and angular parameters (0°, 45° and 90°) were conducted at 10% of the texture area and pump silicone grease.

When point texture was added to the surface of the rotor sample, the friction coefficient and wear quantity of the sample were lower than those of the surface without texture treatment, and the double tongue 0° combination showed the best tribological properties. At this time, the average coefficient of friction and wear is reduced by 22.8% and 62%, 28.6% and 64.8%.

The introduction of texture can effectively improve the tribological performance of progressive screw pumps, and this paper provides important theoretical and experimental support for the design of progressive screw pumps in practical applications.

This paper aims to compare the differences between single- and multi-person interactions in virtual tourism, underpinned by the stimulus-organism-response (S-O-R) framework and media richness theory (MRT).

In this study, quantitative data gathered from questionnaires applied to 558 individuals was analyzed by using partial least squares structural equation modeling. The moderating role of interaction type was tested through multigroup analysis (MGA).

The results showed that vividness positively influenced telepresence, perceived attractiveness and authentic experiences; telepresence positively affected authentic experiences and perceived attractiveness; and authentic experiences and perceived attractiveness positively impacted willingness to visit in both interaction groups. A difference was detected between the two groups in that perceptions of media vividness were more easily transformed into a willingness to visit through telepresence in the multi-person interaction group. Interaction type moderated the effect of vividness on telepresence. The vividness of the media had a more significant effect on telepresence among those who participated in virtual tourism together.

In this study, a model was developed to explain how media vividness affected willingness to visit by considering the relationships between telepresence, authentic experiences and perceived attractiveness in virtual reality, as well as the social interaction aspect.

本研究旨在比较虚拟旅游中单人和多人互动的差异, 基于刺激-有机体-反应（S-O-R）框架和媒介丰富度理论（MRT）。

本研究对 558 名受试者的问卷调查数据进行了定量分析, 采用 PLS-SEM 模型分析, 并通过多群组分分析（MGA）测试了互动类型的调节作用。

研究结果显示, 生动性对临场感、感知吸引力和真实体验有正向影响; 临场感对真实体验和感知吸引力有正向影响; 真实体验和感知吸引力对参观意愿有正向影响。两组之间的差异在于, 在多人互动组中, 媒介生动性更容易通过临场感转化为参观意愿。互动类型调节了生动性对临场感的影响, 参与虚拟旅游的多人群体中, 媒介的生动性对临场感的影响更为显著。

本研究构建了一个模型, 解释了在虚拟现实中, 媒介生动性如何通过临场感、真实体验和感知吸引力的关系影响参观意愿, 同时考虑了社会互动的因素。

This study aims to explore the effect of chief executive officer education on firms’ action timing and acquisition performance in industry merger waves. In addition, this study investigated the moderating influence of CEO duality and firm cash flow on the relationship between education and entry timing.

Following the methodology for determining merger waves in previous studies, the authors identified 16 industry merger waves of Chinese listed firms from 2008 to 2019. Multiple linear regression was employed to examine the hypotheses.

The results showed that higher CEO education was associated with early participation in merger waves. CEO duality negatively moderated the education-entry timing relation. The effect of CEO education on entry timing was more pronounced when firms had higher cash flow. Moreover, more educated CEOs materially enhanced acquisition performance in merger waves.

Entry timing in industry merger waves has important implications, as early movers establish competitive advantages and achieve higher acquisition performance. However, the managerial characteristics determining entry timing have not received adequate attention. Meanwhile, studies examining the effect of CEO education on acquisitions are limited. This study explored the effect of CEO education on firms’ entry timing and acquisition performance in merger waves, thereby contributing to the literature on merger waves and managerial characteristics. This study’s findings regarding the moderators of the education-entry timing relation enrich the literature on corporate governance and agency theory.

The purpose of this paper is to provide an overview of studies published in the Journal of Entrepreneurship in Emerging Economies (JEEE) between 2014 and 2019. The review also provides suggestions for future research in JEEE.

Integrative literature of 90 empirical and conceptual articles published in JEEE between 2014 and 2019. The selected articles were analyzed using content analysis.

Analysis of the 90 published articles shows that JEEE has covered a number of relevant topics related to entrepreneurship and innovation in emerging economies. In particular, scholars have adopted a variety of methods to describe such activities in emerging economies. The review also highlights the lack of comparative studies in JEEE and studies, which significantly take into account or focus on the emerging economy context.

The findings suggest that future scholars wishing to submit to JEEE should consider taking a more detailed account of the emerging context.

Since its first publication in 2014, this study represents the first review of articles found in JEEE. Specifically, the study provides a platform for future scholars wishing to submit to JEEE to take stock of the studies in the journal, thus giving them a better understanding of the field. The study also provides directions regarding areas of possible future research, which might be of interest to scholars wishing to submit to JEEE.

Over the last eight years, the Middle East has experienced a series of high profile conflicts which have resulted in over 5.6 million Syrians forced to migrate to neighbouring countries within the MENA (Middle East and North Africa) region or to Europe. That have exerted huge pressure on hosting countries trying to accommodate refugees in decent shelters and in quick manner. Temporary shelters normally carry a high environmental burden due to their short lifespan, and the majority are fabricated from industrialised materials. This study assesses the carbon impact for a minus carbon experimental refugee house in Sweden using life cycle assessment (LCA) as tool. SimaPro and GaBi software were used for the calculations and the ReCiPe midpoint method for impact assessment. The results show that using local plant-based materials such as straw, reeds and wood, together with clay dug from close to the construction site, can drastically reduce the carbon footprint of temporary shelters and even attain a negative carbon impact of 226.2 kg CO₂ eq/m². Based on the results of the uncertainty importance analysis, the overall global warming potential impact without and with sequestration potential are mostly sensitive to the variability of the GWP impact of wood fibre insulation.

The methodology is designed to calculate the GWP impact of the refugee house over its entire life cycle (production, operation and maintenance and end of life). Then, the sensitivity analysis was performed to explore the impact of input uncertainties (selection of material from the database and the method) on the total GWP impact of the refugee house with and without sequestration. The ISO standards (International Standard 14040 2006; International Standard 14044 2006) divide the LCA framework into four steps of Goal and scope, inventory analysis, impact assessment, and interpretation.

This study has shown an example for proof of concept for a low impact refugee house prototype using straw, reeds, clay, lime and wood as the principle raw materials for building construction. Using natural materials, especially plant-based fibres, as the main construction materials, proved to achieve a minus carbon outcome over the life cycle of the building. The GWP of the shelter house without and with sequestration are found to be 254.7 kg CO₂ eq/m² and -226.2 kg CO₂ eq/m², respectively.

As there are still very few studies concerned with the environmental impact of temporary refugee housing, this study contributes to the pool of knowledge by introducing a complete LCA calculation for a physical house prototype as a proof of concept on how using low impact raw materials for construction combined with passive solutions for heating and cooling can reach a minus carbon outcome. The GWP of the shelter house without and with sequestration are found to be 254.7 kg CO₂ eq/m² and -226.2 kg CO₂ eq/m².

This study aims to assess carbon emissions in urban aged residential buildings in Qingdao, Shandong Province, constructed prior to 2000, and to evaluate retrofitting and rebuilding strategies for potential carbon reduction.

Field investigations and literature reviews were conducted to identify key factors influencing carbon emissions, such as shape coefficient, window-to-wall ratio and envelope structure. A combination of generalization and mathematical statistical methods was used to classify buildings based on construction year, form, structural type and energy-saving goals. Cluster analysis was employed to extract six typical building models.

Results demonstrate that building form complexity positively correlates with carbon emissions per unit area, while longer lifespans reduce emission intensity. Retrofitting exhibits shorter carbon payback periods (1.62–3.92 years) than rebuilding (18.7–49.94 years), indicating superior environmental performance. Pre-1986 buildings are advised for demolition/rebuilding due to limited retrofit benefits. For 1986–1995 buildings, retrofitting is recommended if structurally viable. Post-1996 buildings favor retrofitting over new construction for its shorter payback and lower emissions, enhancing long-term carbon reduction.

This study contributes to the understanding of carbon emissions in urban aged residential buildings by considering various factors and providing specific recommendations for retrofitting and rebuilding strategies tailored to different construction periods. Additionally, it highlights the importance of building form complexity and remaining lifespan in determining carbon emissions, offering insights for sustainable urban development and carbon reduction initiatives.

This paper aims to critically evaluate the role of advanced artificial intelligence (AI)-enhanced image fusion techniques in lung cancer diagnostics within the context of AI-driven precision medicine.

We conducted a systematic review of various studies to assess the impact of AI-based methodologies on the accuracy and efficiency of lung cancer diagnosis. The focus was on the integration of AI in image fusion techniques and their application in personalized treatment strategies.

The review reveals significant improvements in diagnostic precision, a crucial aspect of the evolution of AI in healthcare. These AI-driven techniques substantially enhance the accuracy of lung cancer diagnosis, thereby influencing personalized treatment approaches. The study also explores the broader implications of these methodologies on healthcare resource allocation, policy formation, and epidemiological trends.

This study is notable for both emphasizing the clinical importance of AI-integrated image fusion in lung cancer treatment and illuminating the profound influence these technologies have in the future AI-driven healthcare systems.