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This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

The most challenging aspect of hospital design is the creation of an environment that heals rather than the one acting as a barrier to healing. Much has not been done in the aspect of ascertaining the level of impact “indoor environmental quality (IEQ)” has on building occupants in healthcare facilities. Therefore, this study aims to investigate the impact of IEQ on patients' health and well-being.

The study investigates the hypothesis that four IEQ parameters (thermal quality, acoustic quality, lighting quality and indoor air quality [IAQ]) influence patients' overall satisfaction with the performance of hospital wards. Questionnaire responses were sought from the patients as the main occupants of hospital ward buildings. A proposed weighted structural model for IEQ establishing the relationship between IEQ parameters, patients' overall satisfaction and patients' health outcome was analyzed using structural equation modeling (SEM).

The most influential IEQ parameters on patients' overall satisfaction with IEQ in hospital wards are thermal quality, IAQ and lighting quality. The findings from this study revealed that the parameters of influence on patients' overall satisfaction and health outcomes vary with hospital ward orientation and design configuration.

This study has explored the need for the integration of all factors of IEQ at the building design stage towards providing a hospital environmental setting that reflects occupants' requirements and expectations and also promotes patient healing processes. This should be the focus of architects and healthcare managers and providers.

This study investigates the relationship between self-compassion and life satisfaction, and there is a significant statistical correlation between some dimensions of the self-compassion scale (family, self-kindness, common human feelings and mental alertness).

The researcher used the Self-Compassion scale prepared by Neff (2003) translated by the researchers, in a sample of 150 students in Egypt, and Multidimensional Student’s Life Satisfaction Scale, developed by Huebner et al. (1998) translated by the researchers.

The results of the study showed that self-compassion is high in university students. The study also showed a negative correlation with the dimension of psychological self-judgment and life satisfaction, as it indicated the possibility of predicting life satisfaction through the dimensions of self-compassion, except for the dimensions of isolation and autism, and excessive communication with the self. It also indicated that there are no differences between males and females as far as the variable of self-compassion, as well as the absence of differences between males and females as far as the variable of satisfaction with life is concerned. However, the family dimension showed a difference in favor of males.

The inclusion of extension programs to develop self-compassion for various segments of society in light of the continuing corona pandemic, and paying attention to religious counseling programs that support the use of spiritual values in self-strengthening which is reflected in the strengthening of psychological resilience and thus a sense of satisfaction with life.

This paper sets out to solve a common and crucial fundamental theoretical problem of gray incidence cluster analysis: to [X]={X|ρ(X,Y)≥1−ε0} constitute an approximate classification, it must first be proven that [X]={X|ρ(X,Y)=1} constitutes a rigorous classification.

This paper does not study the concrete expressions of various incidence degrees but rather the perfect correlation essence of such incidence degrees, that is, sufficient and necessary conditions.

For any order difference incidence degree, the similarity incidence degree, the direct proportion incidence degree, the parallel incidence degree and the nearness incidence degree, it is proven that the perfect correlation relation is an equivalence relation. The set composed of all sequences Y that are equivalent to sequences X is studied, that is, the equivalence class of X. The structure and mutual relations of these equivalence classes are discussed, and the topological homeomorphism concept of incidence degree is introduced. The conclusion is obtained that the equivalence classes of the two incidence degrees must be the same when the topological homeomorphism is obtained.

In this paper, only the perfect correlation relation of any order difference incidence degree, the similarity incidence degree, the direct proportion incidence degree, the parallel incidence degree and the nearness incidence degree are studied as equivalent relations.

Not only are the research results of several incidence degrees involved in this paper original but also many other effective incidence degrees have not done this basic research, so this paper opens up a research direction with theoretical significance.

Amid rapid technological progress, the construction industry is embracing Construction 4.0, redefining work practices through emerging technologies. However, the implications of Construction 4.0 technologies to enhancing well-being are still poorly understood. Particularly, the challenge lies in selecting technologies that critically contribute to well-being enhancement. Therefore, this study aims to evaluate the implications of Construction 4.0 technologies to enhancing well-being.

A list of Construction 4.0 technologies was identified from a national strategic plan on Construction 4.0, using Malaysia as a case study. Fourteen construction industry experts were selected to evaluate the implications of Construction 4.0 technologies on well-being using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The expert judgment was measured using linguistic variables that were transformed into fuzzy values. Then, the collected data was analyzed using the following analyses: fuzzy TOPSIS, Pareto, normalization, sensitivity, ranking performance and correlation.

Six Construction 4.0 technologies are critical to enhancing well-being: cloud & real-time collaboration, big data & predictive analytics, Internet of Things, building information modeling, autonomous construction and augmented reality & virtualization. In addition, artificial intelligence and advanced building materials are recommended to be implemented simultaneously as a very strong correlation exists between them.

The novelty of this study lies in a comprehensive understanding of the implications of Construction 4.0 technologies to enhancing well-being. The findings can assist researchers, industry practitioners and policymakers in making well-informed decisions to select Construction 4.0 technologies when targeting the enhancement of the overall well-being of the local construction industry.

This study aims to test the contagion effect of the Tunisian revolution on the Egyptian stock market. Thus, the purpose of this research is to distinguish the contagion effect from the simple interdependence between these markets.

This paper examines the contagion hypothesis between Tunisia and Egypt during the Arab Spring, using a DCC-MGARCH model to capture time-varying contagion effects and dynamic linkages in stock markets. Therefore, to identify the contagion effect from the simple interdependence, the authors apply the pure contagion test developed by Forbes and Rigobon (2002).

The findings indicate a contagion effect, as the EGX 30 index exhibited similar changes, positive or negative, as the Tunindex index during the period of the Tunisian revolution. Moreover, the analysis demonstrates the presence of an interdependence between the Tunisian revolution and the Egyptian market, emphasizing the interconnections between these two economies.

The findings provide investors with a better understanding of financial market dynamics in times of major political unrest, notably on the Tunisian and Egyptian markets. By understanding the contagion effect of the Tunisian revolution on the Egyptian stock market, investors can further explore the complexities of these markets in times of financial crises, which can help mitigate losses and identify strategic investment opportunities.

This study makes two significant contributions to the field. First, it addresses the scarcity of research specifically focused on the contagion effect during the Arab Spring, aiming to fill this gap by testing the contagion effect of the Tunisian revolution on a nearby market. Second, it extends the contagion test of Forbes and Rigobon (2002), which associates “pure” contagion with a significantly higher correlation between markets during a crisis.

The research paper examines the complex relationship between gamification, student engagement and academic performance in educational environments. The study employed a structural equation model that highlights important connections among key constructs within the educational setting.

This research aims to explore the connection between gamification, student engagement and academic performance in educational settings. The study employs various statistical techniques such as factor analysis, Kaiser–Meyer–Olkin (KMO), Bartlett’s test, component transformation matrix, correlation and regression analysis, descriptive statistics, ANOVA, coefficients and coefficient correlations, residual statistics and confirmatory factor analysis (CFA) to analyze the data.

It was found that active participation by the instructor and good time management skills have a positive impact on student engagement levels (β = 0.380, p < 0.001; β = 0.433 and p < 0.001). However, peer interaction does not significantly predict student engagement (β = −0.068 and p = 0.352). Additionally, there is a positive correlation between student engagement and performance (β = 0.280 and p < 0.001).

The study highlights the importance of innovative design to fully utilize gamification. Future research should consider design, user characteristics and educational context. The findings can guide informed decisions about gamification in education, fostering motivation and learning objectives.

The study presents a reliable tool for assessing student engagement and performance in educational settings, demonstrating high Cronbach’s alpha and robust reliability. It identifies student engagement and time management as significant predictors of Global Learning Outcome. The findings can inform decisions on implementing gamification in educational settings, promoting intrinsic motivation and aligning with learning objectives.

The research highlights the transformative impact of gamification on educational practices, highlighting its potential to enhance student experiences, motivate, promote diversity and improve long-term academic performance, highlighting the trend of integrating technology into education.

In today’s ever-changing education landscape, it is essential to incorporate innovative techniques to keep students engaged and enthusiastic about learning. Gamification is one such approach that has become increasingly popular. It is a concept that takes inspiration from the immersive world of games to enhance the overall learning experience.

This study aims to establish a reliable index to identify interdisciplinary breakthrough innovation effectively. We constructed a new index, the D_Div index, for this purpose.

The D_Div index incorporates the degree of interdisciplinarity in the breakthrough index. To validate the index, a data set combining the publication records and citations of Nobel Prize laureates was divided into experimental and control groups. The validation methods included sensitivity analysis, correlation analysis and effectiveness analysis.

The sensitivity analysis demonstrated the D_Div index’s ability to differentiate interdisciplinary breakthrough papers from various categories of papers. This index not only retains the strengths of the existing index in identifying breakthrough innovation but also captures interdisciplinary characteristics. The correlation analysis revealed a significant correlation (correlation coefficient = 0.555) between the interdisciplinary attributes of scientific research and the occurrence of breakthrough innovation. The effectiveness analysis showed that the D_Div index reached the highest prediction accuracy of 0.8. Furthermore, the D_Div index outperforms the traditional DI index in terms of accuracy when it comes to identifying interdisciplinary breakthrough innovation.

This study proposed a practical and effective index that combines interdisciplinary and disruptive dimensions for detecting interdisciplinary breakthrough innovation. The identification and measurement of interdisciplinary breakthrough innovation play a crucial role in facilitating the integration of multidisciplinary knowledge, thereby accelerating the scientific breakthrough process.

Bearings play a critical role in the reliable operation of induction machines, and their failure can lead to significant operational challenges and downtime. Detecting and diagnosing these defects is imperative to ensure the longevity of induction machines and preventing costly downtime. The purpose of this paper is to develop a novel approach for diagnosis of bearing faults in induction machine.

To identify the different fault states of the bearing with accurately and efficiently in this paper, the original bearing vibration signal is first decomposed into several intrinsic mode functions (IMFs) using variational mode decomposition (VMD). The IMFs that contain more noise information are selected using the Pearson correlation coefficient. Subsequently, discrete wavelet transform (DWT) is used to filter the noisy IMFs. Second, the composite multiscale weighted permutation entropy (CMWPE) of each component is calculated to form the features vector. Finally, the features vector is reduced using the locality-sensitive discriminant analysis algorithm, to be fed into the support vector machine model for training and classification.

The obtained results showed the ability of the VMD_DWT algorithm to reduce the noise of raw vibration signals. It also demonstrated that the proposed method can effectively extract different fault features from vibration signals.

This study suggested a new VMD_DWT method to reduce the noise of the bearing vibration signal. The proposed approach for bearing fault diagnosis of induction machine based on VMD-DWT and CMWPE is highly effective. Its effectiveness has been verified using experimental data.

The sustainable development goal (SDG 17) is to strengthen the means of implementation and revitalise the global partnership for sustainable development. Partnership is a key strategy for acquiring skills, information and private finance for developing critical infrastructure projects. Existing studies have mostly concentrated on identifying critical success factors (CSFs) for successfully delivering public–private partnerships (PPPs) projects, but the interrelationships among CSFs expected from stakeholders have garnered less attention. The purpose of this study is to examine the interconnections among CSFs of PPP projects while keeping the public in mind, as well as the influencing routes that contribute to success in the PPP implementation process.

The study uses a mixed-method approach that involves both quantitative and qualitative methods of data collection. The data for the study were collected through a well-structured questionnaire from the respondents who are directly or indirectly associated with the PPP project implementation process. The CSF’s framework was built using a literature study and expert interviews; nine hypotheses were developed and evaluated using structural equation modelling. Random and purposive sampling techniques were used for the respondents who were directly or indirectly associated with the PPP project implementation process.

The findings of this study reveal that the relationship between public and private partners is more adherent than collaborative, with unequal responsibilities, powers and resources distributed among the parties involved. The relevance of state rules, the PPP directive and policies in PPP implementation is supported by the positive connection between favourable environments (Fav_Env) and government attributes (Gov_Atr; the path coefficient is 0.405). Moreover, government attributes have a favourable influence on private company attributes (Pvt_Atr; the path coefficient is 0.198), showing that the state plays a substantial role in the private sector’s decision-making process in PPP. The long-term sustainability and success of a PPP project are dependent on the established interrelationships between CSFs.

The established interrelationships between CSFs will contribute to the long-term viability and success of a PPP project. Since PPP is still in its infancy in India, the study of CSFs in PPPs and their interrelationships will help policymakers and other stakeholders better understand the major individual factors impacting the success or failure of PPP initiatives.

Because PPP is still in its infancy in India, the study of CSFs in PPPs and their interrelationships will help policymakers and other stakeholders to better understand the major individual factors impacting the success or failure of PPP initiatives. A key implication of the study borders on providing a better understanding of the relationships between CSFs and public engagement. This is also critical for the long-term viability of PPPs and the enhancement of public service quality.