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The purpose of this paper is to identify the historical trends and status of the national development of artificial intelligence (AI) from a nationwide perspective and to enable governments at different administrative levels to promote AI development through policymaking.

This paper analyzed 248 Chinese AI policies (36 issued by the state agencies and 212 by the regional agencies). Policy bibliometrics, policy instruments and network analysis were used to reveal the AI policy patterns. Three aspects were analyzed: the spatiotemporal distribution of issued policies, the policy foci and instruments of policy contents and the cooperation and citation among policy-issuing agencies.

Results indicate that Chinese AI development is still in the initial phase. During the policymaking processes, the state and regional policy foci have strong consistency; however, the coordination among state and regional agencies is supposed to be strengthened. According to the issuing time of AI policies, Chinese AI development is in accordance with the global situation and has witnessed unprecedented growth in the last five years. And the coastal provinces have issued more targeted policies than the middle and western provinces. Governments at the state and regional levels have emphasized familiar policy foci and played the role of policymakers, along with regional governments that also functioned as policy executors as well. According to the three-dimension instruments coding, the authors found an uneven structure of policy instruments at both levels. Furthermore, weak cooperation appears at the state level, while little cooperation is found among regional agencies. Regional governments cite state policies, thus leading to the formation of top-down diffusion, lacking bottom-up diffusion.

The paper contributes to the literature by characterizing policy patterns from both external attributes and semantic contents, thus revealing features of policy distribution, contents and agencies. What is more, this research analyzes Chinese AI policies from a nationwide perspective, which contributes to clarifying the overall status and multi-level relationships of policies. The findings also benefit the coordinated development of governments during further policymaking processes.

The purpose of this paper is to study the mechanisms governing dynamic changes in relational and contractual governance at different stages of government-funded mega construction projects (MCPs) by studying their different effects on project performance and participants’ opportunism.

Partial least squares structural equation modeling was used to test eight hypotheses based on data collected from 147 respondents in different participating organizations in Chinese MCPs.

First, contractual governance has a stronger positive impact on project performance than relational governance in the early stage of MCPs, while relational governance exerts more positive effects on project performance than contractual governance in the middle and late stages. Second, opportunism is a mediator variable between governance mechanisms and project performance, and relational governance is more effective than contractual governance in restricting opportunism.

In contrast to a static analysis of project governance mechanisms, this study examines dynamic changes in the governance mechanisms of MCPs in the Chinese context by considering the mediating role of opportunism as well as guanxi as an element of relational governance, thus filling in gaps in the literature on MCP governance and contributing to the development of MCP management theory.

The purpose of this study is to find the multi-factor influence law of stress, strain rate and sulfate-reducing bacteria (SRB) on X70 pipeline steel in a simulated solution of sea mud and the order of influence of the three factors on X70 steel to develop a scientific basis for pipeline corrosion protection.

This paper studied the effects of stress, strain rate and SRB on the X70 pipeline steel corrosion behavior in simulated sea mud solution through orthogonal testing, electrochemical experiments and morphological observations.

The results of this study showed that stress proved to be the most relevant element for corrosion behavior, followed by SRB and strain rate. At high stresses (301 MPa and 576 MPa), stress dominated the corrosion behavior of X70 pipeline steel. However, at low stress (82 MPa), SRB played the most important role.

Subsea pipelines are in a very complex environmental regime that includes stress, strain rates and SRB, which often cause pipeline pitting and perforation. However, most scholars have only looked into the influence of single factors on metal corrosion. So, the single-factor experimental results of previous studies could hardly be applied to actual working conditions. There is an urgent need to understand the multi-factor influence law of stress, strain and SRB acting together on the pipeline corrosion behavior, especially to determine the dominant factor.

The purpose of this paper is to synthesise a disperse dye based on benzisothiazole and to characterise its crystal morphology, dispersing stability, to study the relationship between the chemical structure and the dyeing property of the dye.

The disperse dye based on benzisothiazole, 3-(3-methyl-4-N-ethyl-N-benzyl-phenyldiazenyl)-5-nitro-2,1-benzisothiazoles, was synthesized. The disperse dye based on benzisothiazole, 3-(3-methyl-4-N-ethyl-N-benzyl-phenyldiazenyl)-5-nitro-2,1-benzisothiazoles, was synthesised. The chemical structure of the dye obtained was characterised by infrared spectrum Fourier transform infrared spectroscopy and nuclear magnetic resonance (1HNMR), and the crystal morphology was observed by Field Emission Scanning Electron Microscopy. Sodium salt of polycondensated naphthalenesulphonic acid (dispersing agent sodium salt of polycondensated naphthalenesulphonic acid [MF]) and a sulphonated amino polyether (anionic surfactant B600) were employed to grind and disperse the dye crystals. The dispersion property of the dye particles was characterised. Dyeing property of the dispersion system was also studied.

The dye formed spherical crystals that were made up of a large number of acicular crystals similar to spherical chrysanthemum. The crystals had warping crystal centres inside the spheres. The particle sizes of the dispersion with the mixture of B600 and MF had an uniform distribution and were smaller than that of the dispersion with only single dispersing agent MF. Dyeing with the dispersion system had an excellent reproducibility under alkalinic condition.

An alkalinic dyeing method for poly(ethylene terephthalate) (PET) with disperse dyes as a cleaner wet process had been developed. Such a process combined pretreatment and dyeing process using the alkali-stable disperse dyes and reduced the consumption of water and energy and improved production efficiency.

The crystal morphology, dispersion and dyeing properties of the synthesised disperse dye for dyeing PET fabric under alkalinic condition were discussed. This disperse dye has an important potential application in alkalinic dyeing method.

The review examines the existing literature on blockchain-based small and medium enterprise (SME) finance and highlights its trend, themes, opportunities and challenges. Based on these factors, the authors create a framework for the existing literature on blockchain-based SME financing and lay down future research paths.

The review follows a systematic approach. It includes 53 articles encompassing multiple dimensions of blockchain-based SME finance, including peer-to-peer lending platforms, supply chain finance (SCF), decentralized lending protocols and tokenization of assets. The review critically evaluates these approaches' theoretical underpinnings, empirical evidence and practical implementations.

The review demonstrates that blockchain-based SME finance holds significant promise in addressing the credit gap by leveraging blockchain technology's decentralized and transparent nature. Benefits identified include reduced information asymmetry, improved access to financing, enhanced credit assessment processes and increased financial inclusion. However, the literature acknowledges several challenges and limitations, such as regulatory uncertainties, scalability issues, operational complexities and potential security risks.

The article contributes to the growing knowledge of blockchain-based SME finance by synthesizing and evaluating the existing literature. It also provides a framework for the existing literature in the area and future research paths. The study offers insights for researchers, policymakers and practitioners seeking to understand the potential of blockchain technology in filling the SME credit gap and fostering economic development through improved access to finance for SMEs.

The purpose of this paper is to calculate the Hugoniot relations of polyurea; also to investigate the atomic-scale energy change, the related chain conformation evolution and the hydrogen bond dissociation of polyurea under high-speed shock.

The atomic-scale simulations are achieved by molecular dynamics (MD). Both non-equilibrium MD and multi-scale shock technique are used to simulate the high-speed shock. The energy dissipation is theoretically derived by the thermodynamic and the Hugoniot relations. The distributions of bond length, angle and dihedral angle are used to characterize the chain conformation evolution. The hydrogen bonds are determined by a geometrical criterion.

The Hugoniot relations calculated are in good agreement with the experimental data. It is found that under the same impact pressure, polyurea with lower hard segment content has higher energy dissipation during the shock-release process. The primary energy dissipation way is the heat dissipation caused by the increase of kinetic energy. Unlike tensile simulation, the molecular potential increment is mainly divided into the increments of the bond energy, angle energy and dihedral angle energy under shock loading and is mostly stored in the soft segments. The hydrogen bond potential increment only accounts for about 1% of the internal energy increment under high-speed shock.

The simulation results are meaningful for understanding and evaluating the energy dissipation mechanism of polyurea under shock loading, and could provide a reference for material design.

The purpose of this study was to analyze importance of artificial intelligence (AI) in education and its emphasis on assessment and adversity quotient (AQ).

The study utilizes a systematic literature review of over 141 journal papers and psychometric tests to evaluate AQ. Thematic analysis of quantitative and qualitative studies explores domains of AI in education.

Results suggest that assessing the AQ of students with the help of AI techniques is necessary. Education is a vital tool to develop and improve natural intelligence, and this survey presents the discourse use of AI techniques and behavioral strategies in the education sector of the recent era. The study proposes a conceptual framework of AQ with the help of assessment style for higher education undergraduates.

Research on AQ evaluation in the Indian context is still emerging, presenting a potential avenue for future research. Investigating the relationship between AQ and academic performance among Indian students is a crucial area of research. This can provide insights into the role of AQ in academic motivation, persistence and success in different academic disciplines and levels of education. AQ evaluation offers valuable insights into how individuals deal with and overcome challenges. The findings of this study have implications for higher education institutions to prepare for future challenges and better equip students with necessary skills for success. The papers reviewed related to AI for education opens research opportunities in the field of psychometrics, educational assessment and the evaluation of AQ.

This paper seeks to examine the relationship between Turkish ethnic entrepreneurs' socio‐cultural characteristics (namely education, experience and religion) and the entrepreneurial orientation of their firms.

The study collected data through 139 face‐to‐face structured interviews with Turkish ethnic entrepreneurs in London, UK.

The study illustrates that educational attainment of an entrepreneur makes a positive impact on a firm's entrepreneurial orientation. Educational attainment equips business owners with the skills and reflective mindsets of understanding customers and responding to their needs. Previous business experience of the entrepreneur also impacts positively upon a firm's entrepreneurial orientation, while religion of the entrepreneur does not have a significant impact on the firm's entrepreneurial orientation.

This paper reports findings based on Turkish ethnic entrepreneurs in London. Therefore, care should be taken in making generalisations from the sample.

This paper identifies those socio‐cultural attributes that entrepreneurs can capitalise on in order to enhance the entrepreneurial orientation of their firms.

The paper fills in a glaring gap by providing empirical evidence about the relationship between socio‐cultural characteristics of entrepreneurs and their small firms' entrepreneurial orientation.

The paper posits that a solution for businesses to use privacy-friendly data repositories for its customers’ data is to change from the traditional centralized repository to a trusted, decentralized data repository. Blockchain is a technology that provides such a data repository. However, the European Union’s General Data Protection Regulation (GDPR) assumed a centralized data repository, and it is commonly argued that blockchain technology is not usable. This paper aims to posit a framework for adopting a blockchain that follows the GDPR.

The paper uses the Levy and Ellis’ narrative review of literature methodology, which is based on constructivist theory posited by Lincoln and Guba. Using five information systems and computer science databases, the researchers searched for studies using the keywords GDPR and blockchain, using a forward and backward search technique. The search identified a corpus of 416 candidate studies, from which the researchers applied pre-established criteria to select 39 studies. The researchers mined this corpus for concepts, which they clustered into themes. Using the accepted computer science practice of privacy by design, the researchers combined the clustered themes into the paper’s posited framework.

The paper posits a framework that provides architectural tactics for designing a blockchain that follows GDPR to enhance privacy. The framework explicitly addresses the challenges of GDPR compliance using the unimagined decentralized storage of personal data. The framework addresses the blockchain–GDPR tension by establishing trust between a business and its customers vis-à-vis storing customers’ data. The trust is established through blockchain’s capability of providing the customer with private keys and control over their data, e.g. processing and access.

The paper provides a framework that demonstrates that blockchain technology can be designed for use in GDPR compliant solutions. In using the framework, a blockchain-based solution provides the ability to audit and monitor privacy measures, demonstrates a legal justification for processing activities, incorporates a data privacy policy, provides a map for data processing and ensures security and privacy awareness among all actors. The research is limited to a focus on blockchain–GDPR compliance; however, future research is needed to investigate the use of the framework in specific domains.

The paper posits a framework that identifies the strategies and tactics necessary for GDPR compliance. Practitioners need to compliment the framework with rigorous privacy risk management, i.e. conducting a privacy risk analysis, identifying strategies and tactics to address such risks and preparing a privacy impact assessment that enhances accountability and transparency of a blockchain.

With the increasingly strategic use of data by businesses and the contravening growth of data privacy regulation, alternative technologies could provide businesses with a means to nurture trust with its customers regarding collected data. However, it is commonly assumed that the decentralized approach of blockchain technology cannot be applied to this business need. This paper posits a framework that enables a blockchain to be designed that follows the GDPR; thereby, providing an alternative for businesses to collect customers’ data while ensuring the customers’ trust.

The purpose of this paper is to propose a scenario-based grey methodology using clustering and optimizing with imprecise and uncertain body size data in an emergency assembly point area to assign the people on a campus to reach the emergency assembly points under uncertain disaster times.

Grey clustering and a new grey p-median linear programming model are developed to determine which units to assign to the pre-determined assembly points for a main campus in case of a disaster. The models have two scenarios: 70 and 100% occurrence capacities of administrative and academic personnel and students.

In this study, the academic and administrative units have been assigned to determine five different emergency assembly points on the main campus by using the numbers of the academic and administrative personnel and student and distances of the units to the assembly point areas of each other. The alternative solutions are obtained effectively by evaluating capacity utilization rates in the scenarios.

It is often unclear when disasters can occur and therefore, a preliminary preparation time must be required to minimize the risk. In the case of natural, man-made (unnatural) or technological disasters, the people are required to defend themselves and move away from the disaster area as soon as possible in a proper direction. The proposed assignment model yields a final solution that effectively eliminates uncertainty regarding the selection of emergency assembly points for administrative and academic staff as well as students, in the event of disasters.

Grey clustering suggests an assignment plan and concurrently, an investigation is underway utilizing the grey p-median linear programming model. This investigation aims to optimize various scenarios and body sizes concerning emergency assembly areas. All campus users who are present at the disaster in units of the campus are getting uncertainty about which emergency assembly point to use, and with this study, the vital risks aim to be ultimately reduced with reasonable plans.