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This paper aims at building a discharge model for the power cable bellows based on plasma energy deposition and analyzing the discharge ablation problem.

Aiming at the multiphysical mechanism of the discharge ablation process, a multiphysical field model based on plasma energy deposition is established to analyze the discharge characteristics of the power cable bellows. The electrostatic field, plasma characteristics, energy deposition and temperature field are analyzed. The discharge experiment is also carried out for result validation.

The physical mechanism of the bellows ablative effect caused by partial discharge is studied. The results show that the electric field intensity between the aluminum sheath and the buffer layer easily exceeds the pressure resistance value of air breakdown. On the plasma surface of the buffer layer, the electron density is about 4 × 1,019/m³, and the average temperature of electrons is about 3.5 eV. The energy deposition analysis using the Monte Carlo method shows that the electron range in the plasma is very short. The release will complete within 10 nm, and it only takes 0.1 s to increase the maximum temperature of the buffer layer to more than 1,000 K, thus causing various thermal effects.

Its physical process involves the distortion of electric field, formation of plasma, energy deposition of electrons, and abrupt change of temperature field.

A zero-day vulnerability is a complimentary ticket to the attackers for gaining entry into the network. Thus, there is necessity to device appropriate threat detection systems and establish an innovative and safe solution that prevents unauthorised intrusions for defending various components of cybersecurity. We present a survey of recent Intrusion Detection Systems (IDS) in detecting zero-day vulnerabilities based on the following dimensions: types of cyber-attacks, datasets used and kinds of network detection systems.

Purpose: The study focuses on presenting an exhaustive review on the effectiveness of the recent IDS with respect to zero-day vulnerabilities.

Methodology: Systematic exploration was done at the IEEE, Elsevier, Springer, RAID, ESCORICS, Google Scholar, and other relevant platforms of studies published in English between 2015 and 2021 using keywords and combinations of relevant terms.

Findings: It is possible to train IDS for zero-day attacks. The existing IDS have strengths that make them capable of effective detection against zero-day attacks. However, they display certain limitations that reduce their credibility. Novel strategies like deep learning, machine learning, fuzzing technique, runtime verification technique, and Hidden Markov Models can be used to design IDS to detect malicious traffic.

Implication: This paper explored and highlighted the advantages and limitations of existing IDS enabling the selection of best possible IDS to protect the system. Moreover, the comparison between signature-based and anomaly-based IDS exemplifies that one viable approach to accurately detect the zero-day vulnerabilities would be the integration of hybrid mechanism.

This study determines the nexus between spiritual leadership and psychological safety (PS). The authors explore the mediating role of PS and knowledge sharing to offer insights on how spiritual leadership can be advanced to better understand and support intellectual capital.

Data were collected using convenience sampling from the Pakistani automobile manufacturing industry. SPSS statistical software was used for descriptive analysis and hypotheses were tested by using the partial least square-structural equation modeling method.

The results demonstrate that spiritual leadership has a significant positive impact on PS; PS has a positive impact on knowledge sharing (KS) and KS has a positive impact on intellectual capital. Furthermore, PS mediates between spiritual leadership and KS. KS mediates between PS and human, social and organizational capital. Spiritual leadership also affects outside the boundaries of the organization and builds strong social relations with suppliers, buyers, etc.

This study provides a deeper understanding of spiritual leadership in the context of KS and intellectual capital in the automobile sector of Pakistan.

This study encourages managers to nurture a philosophy of altruistic love that exerts a positive influence on employees. It will enrich their experience and promote a culture of KS.

This study has social implications for organizations seeking to situate their inclusive goals in society. The findings of this study can help promote harmony as employees who feel psychologically safe are more willing to spread it in society.

This study theoretically contributes the big picture that how spiritual leadership contributes to intellectual capital and adds to the literature on the topic.

The purpose of this paper is to conduct a comprehensive study on building, fire and evacuation, so as to effectively improve the efficiency of building fire evacuation and the management level of fire evacuation site. Make up for the difficulties of BIM technology in effectively connecting building information and fire data.

First, this paper establishes a fire model and an evacuation model based on BIM information. Then, the safety index (SI) is introduced as a comprehensive index, and the IRI is established by integrating the SI function to evaluate the safety of evacuation routes. Based on these two indices, the IRI-based fire evacuation model is established.

This study offers an Improved Risk Index (IRI)-based fire evacuation model, which may achieve effective evacuation in fire scenes. And the model is verified by taking the fire evacuation of a shopping center building as an example.

This paper proposes a fire evacuation principle based on IRI, so that the relevant personnel can comprehensively consider the fire factors and evacuation factors to achieve the optimization of building design, thereby improving the fire safety of buildings.

Because of the advantages of high deposition efficiency and low manufacturing cost compared with other additive technologies, robotic wire arc additive manufacturing (WAAM) technology has been widely applied for fabricating medium- to large-scale metallic components. The additive manufacturing (AM) method is a relatively complex process, which involves the workpiece modeling, conversion of the model file, slicing, path planning and so on. Then the structure is formed by the accumulated weld bead. However, the poor forming accuracy of WAAM usually leads to severe dimensional deviation between the as-built and the predesigned structures. This paper aims to propose a visual sensing technology and deep learning–assisted WAAM method for fabricating metallic structure, to simplify the complex WAAM process and improve the forming accuracy.

Instead of slicing of the workpiece modeling and generating all the welding torch paths in advance of the fabricating process, this method is carried out by adding the feature point regression branch into the Yolov5 algorithm, to detect the feature point from the images of the as-built structure. The coordinates of the feature points of each deposition layer can be calculated automatically. Then the welding torch trajectory for the next deposition layer is generated based on the position of feature point.

The mean average precision score of modified YOLOv5 detector is 99.5%. Two types of overhanging structures have been fabricated by the proposed method. The center contour error between the actual and theoretical is 0.56 and 0.27 mm in width direction, and 0.43 and 0.23 mm in height direction, respectively.

The fabrication of circular overhanging structures without using the complicate slicing strategy, turning table or other extra support verified the possibility of the robotic WAAM system with deep learning technology.

In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

The purpose of this paper is to examine the impact of trade openness on the cost of financial intermediation and bank performance. Developed and developing countries are currently pursuing trade openness to achieve higher bank performance with less intermediation costs.

In attaining the study's objectives, several regression methodologies were employed (i.e. system generalized method of moments (GMM), fixed effect, pooled ordinary least squares (OLS) and vector error correction model (VECM)). The authors tested the hypothesis on data of 885 banks from BRICS countries, which span 18 years (2000–2017).

The results from this robust study showed that embedding higher trade openness reduces financial intermediation costs and improves banks' performance. The results remain robust following the use of different estimation methods and alternative variables as proxies. In addition, results were still valid upon considering bank level, industry level and country level as control variables. It was also observed that the relation pattern holds its rigidity during “good” and “bad” times (i.e. the global financial crisis).

The results provide better references for bank regulators, academics and policymakers to take advantage of the low financial intermediation costs resulting from trade openness.

This study aims to know the tactician role of financial technology (FinTech) in the field of accounting and auditing through contextualized systematic literature review by using bibliometric analysis.

The qualitative bibliometric analysis includes studies from 2017 to 2021 using the Scopus and Web of Science databases, which yielded 277 published papers with the keywords, FinTech accounting and auditing. The contextualized systematic literature review greatly helped in clarifying the content within each cluster.

The study identified the tactician role of fintech primarily in the accounting and auditing professional field. Fintech is still in its inception, with continual development and implementation taking place especially, in the auditing field. The findings also confirm that FinTech can produce a confluence between various research areas, including accounting, auditing, business finance, economics, management and business field.

The study describes the tactician role of FinTech and its huge possibility for future study in the accounting and auditing field among professionals, academics and regulators.

This study be able to help accounting professionals, policymakers and government regulators to establish policy development, as this research emphasizes the tactician role of FinTech in the accounting and auditing field.

FinTech in accounting and auditing might add to the existing field of FinTech in the IR4.0 era that give benefits to different players such as policymakers, governments, researchers, FinTech entrepreneurs and practicing professionals.

To the best of the author’s knowledge, little focus has been given about FinTech in the accounting and auditing field using bibliometric analysis. The insights of systematic literature review provide researchers on FinTech among practicing professionals and offer opportunities for further scientific endeavours.

Cross operation is a common operation method in the building construction process nowadays. Due to the crossover, each other's operations are disturbed, and risks also interact. This superimposed relationship of risks is worthy of attention. The study aims to develop a model for analyzing cross-working risks. This model can quantify the correlation of various risk factors.

The concept of cross operation and the cross types involved are clarified. The risk factors were extracted from cross-operation accidents. The association rule mining (ARM) was used to analyze the results of various cross-types accidents. With the help of visualization tools, the intensity distribution and correlation path of the relationship between each factor were obtained. A complete cross-operation risk analysis model was established.

The application of ARM method proves that there are obvious risk correlation deviations in different types of cross operations. A high-frequency risk common to all cross operations is on-site safety inspection and process supervision, but the subsequent problems are different. Cutting off the high-lift risk chain timely according to the results obtained by ARM can reduce or eliminate the danger of high-frequency risk factors.

This is the first systematic analysis of cross-work risk in the construction. The study determined the priority of risk management. The results contribute to targeted cross-work control to reduce accidents caused by cross-work.