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This study aims to examine the association between Iranian auditors' narcissism and the auditors' professional skepticism.

The authors' sample is comprised of 355 professional auditors working in the private and public sectors in Iranian firms in 2022. The authors use cross-sectional multivariate regression as the main methodology, along with the structural equation modeling (SEM) technique.

The authors find that a higher level of narcissism leads to a greater level of professional skepticism among auditors, which ultimately can enhance the quality of the audit process. The results provided via the robustness tests also supported this finding.

The authors' findings further the understanding of the role of narcissistic personality traits in improving professional skepticism among auditors of an Islamic and emerging country. In addition, audit firms and audit partners can also consider the findings of this study and enhance the effectiveness of audit processes by assigning appropriate employees with certain personalities to specific tasks.

This study aims investigate in-service teachers’ perspectives on the integration of ChatGPT, an artificial intelligence (AI)-driven chatbot, into United Arab Emirates (UAE) private schools. As the UAE progresses towards a knowledge-based economy, aligning with the goals of the UAE 2030 vision, this research assesses the capacity of ChatGPT to enhance the educational experience within the framework of technological pedagogical content knowledge.

A mixed-methods approach is used, combining a survey assessing teachers’ attitudes and a thematic analysis of open-ended responses, to explore the effectiveness, challenges and pedagogical implications of ChatGPT’s use in the classroom.

Findings reveal that teachers value ChatGPT for its potential to individualize learning and streamline the creation of educational materials, aligning with the shift towards student-centred approaches and the demands of 21st-century skills. However, significant challenges are noted, including ethical concerns, the need for reliable content and a necessity for extensive professional development to fully realize ChatGPT’s benefits.

While ChatGPT transforms teaching and learning practices, realizing this potential requires addressing critical issues through adaptive policy-making, continuous educator training and thoughtful integration into the curriculum.

The study highlights the importance of a collaborative approach to dealing with the details of AI in education, ensuring that advancements like ChatGPT align with the evolving educational paradigms of the UAE.

In this study, a different approach is introduced to generate the kinetic sub-model for the modeling of solid-state pyrolysis reactions based on the thermogravimetric (TG) experimental data over a specified range of heating rates. Gene Expression Programming (GEP) is used to produce a correlation for the single-step global reaction rate as a function of determining kinetic variables, namely conversion, temperature, and heating rate.

For a case study on the coal pyrolysis, a coefficient of determination (R²) of 0.99 was obtained using the generated model according to the experimental benchmark data. Comparison of the model results with the experimental data proves the applicability, reliability, and convenience of GEP as a powerful tool for modeling purposes in the solid-state pyrolysis reactions.

The resulting kinetic sub-model takes advantage of particular characteristics, to be highly efficient, simple, accurate, and computationally attractive, which facilitates the CFD simulation of real pyrolizers under isothermal and non-isothermal conditions.

It should be emphasized that the above-mentioned manuscript is not under evaluation in any journals and submitted exclusively for consideration for possible publication in this journal. The generated kinetic model is in the final form of an algebraic correlation which, in comparison to the conventional kinetic models, suggests several advantages: to be relatively simpler, more accurate, and numerically efficient. These characteristics make the proposed model computationally attractive when used as a sub-model in CFD applications to simulate real pyrolizers under complex heating conditions.

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.

To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.

The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.

The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

This study aims to define a set of assumptions for testing the four factors tested statistically to determine information-seeking anxiety based on quantitative data.

The developed questionnaire was distributed among graduate university students in Zhenjiang City to find and confirm the factor affecting information-seeking anxiety. The exploratory factor analysis and confirmatory factor analysis technique has been applied to the sample data set of 329 sample size. Jamovi and SPSS, statistical analysis software, were used to determine the study validity indices.

This study shows that thematic anxiety, quality of resources anxiety, information communication technology anxiety and library anxiety have a significant effect on information-seeking anxiety.

This study highlights the four factors, i.e. library anxiety, information and communication technology (ICT) anxiety, thematic anxiety and the quality of resources cause information-seeking anxiety among graduate students.

In this age of the digital world, information-seeking anxiety plays a vital role in the vicious circle of seeking behavior. Therefore, to break through the vicious loop of seeking behavior with only information-seeking anxiety as a cure, concentrate on information-seeking anxiety. This study found that thematic anxiety, ICT anxiety, library anxiety and quality of resources anxiety significantly affect information-seeking anxiety.

Hepatitis C is one of the major health issues in both developed and developing countries. Hepatitis C virus (HCV) infection is more common in prisoners than in the general population. The purpose of this study was to determine the prevalence of HCV and its associated risk factors in Iranian male prisoners in Tehran.

In this cross-sectional study, the authors investigated the frequency and risk factors of hepatitis C infection among male prisoners in the Great Tehran Prison. Information on risk factors including the length of imprisonment, previous history of imprisonment, history of drug injection, history of tattooing, history of piercing, history of high-risk sex and family history of hepatitis C were extracted from patients’ records. To evaluate HCV status, blood samples were collected and tested.

In this study, 179 participants were included. Nine participants (5.0%, 95% CI, 2.3-9.3) were positive for hepatitis C. HCV infection was not significantly associated with age, marital status, education, previous history of imprisonment, length of imprisonment, piercing and high-risk sex; however, there was a significant association between a history of tattooing and a history of injecting drug use and Hepatitis C.

The prevalence of hepatitis C among male prisoners in Great Tehran Prison was 5% in this study, similar to recent studies on prisoners in Tehran. A history of drug injections as well as tattooing were the most important risk factors for hepatitis C in male prisoners.

This paper examines the effect of ESG ratings and its dimensions (environmental, social and governance) on the financial performance of JSE-listed firms included in FTSE/JSE Responsible Investment Index.

The paper employs panel data covering 40 JSE-listed firms included in FTSE/JSE Responsible Investment Index between 2015 and 2019. The paper employs the two-stage least squares (2SLS) instrumental variable regression technique to estimate the effect of ESG ratings and its dimensions (environmental, social and governance) on both accounting- and market-based performance indicators.

The results of the two-stage least squares instrumental estimation analysis reveal that investment in ESG initiatives improves both accounting- and market-based indicators of financial performance. Of the ESG pillars, the paper finds environmental initiatives improves firms' financial bottom line and market performance, while a firm's social and governance practices are observed to have no effect on a firm's accounting and market performance measures.

The insights from this study proffers policy implications for firms' management, investors and regulatory authorities.

As far as the authors are concerned, this paper presents the first empirical analysis on the contribution of ESG ratings on financial performance in South Africa.

Climate change has led to a rise in the frequency, intensity and scope of droughts, posing significant implications for businesses. This study examines the impact of local community drought levels on audit pricing. Additionally, it explores the moderating effects of high-tech industries, auditor busyness and the level of local community concern regarding the drought crisis.

This study employs a mixed-methods approach to rigorously test the research hypotheses. The quantitative phase of the study utilizes a sample of 1,278 firm-year observations from Iran’s capital market. For the analysis of the quantitative data, ordinary least squares regression with clustered robust standard errors is used. Additionally, this research supplements its quantitative findings with qualitative evidence obtained through semi-structured interviews with 19 Iranian audit partners.

The results suggest that firms operating in provinces facing severe droughts experience notably higher audit fees. Furthermore, the positive relationship between drought and audit fees is weakened when auditors are busy, local community concern regarding the drought crisis is high or the firm operates within high-tech industries. These findings are supported by a range of robustness checks and qualitative evidence gathered from the field.

This research contributes to the growing literature on climate change by examining the influence of local community drought levels on audit pricing within an Iranian context. Additionally, our study sheds light on how high-tech industries, auditor workload and the level of local community concern regarding the drought crisis moderate the relationship between drought and audit fees. Importantly, our study pioneers in providing mixed-methods evidence of the association between drought severity and audit fees.

This study aims to explore the determinants that impact state Islamic University/Perguruan Tinggi Keagamaan Islam Negeri students’ intention to adopt online cash waqfs. In doing so, this study integrates knowledge of cash waqf and trust variables within the theory of planned behavior (TPB), allowing an examination of the mediating role of TPB variables and trust within the relationship between knowledge of cash waqf and intention for online cash waqf behavior.

To carry out an empirical analysis, the authors developed a well-structured questionnaire and distributed it to a group of students currently enrolled in PTKIN, obtaining 443 usable responses. The partial least squares-structural equation modeling (PLS-SEM) technique was used for the dual purposes of data analysis and hypothesis testing.

This study demonstrates that factors such as attitude, subjective norms, perceived behavioral control, trust and knowledge of cash waqf have a significant and favorable influence on the intention to donate through e-cash waqf. Knowledge of cash waqf impacts attitudes, subjective norms, perceived behavioral control and trust. The final analysis shows that attitude, subjective norms, perceived behavioral control and trust partially mediate the relationship between knowledge and intention in the online cash waqf context.

The aforementioned elucidates the paramount importance of trust in shaping individuals’ tendencies to engage in cash waqfs. The insights mentioned have the potential to be used by cash waqf establishments to promote transparency and accountability, ultimately bolstering the confidence of potential donors.

The concepts of waqf and the use of online cash waqf as a means of donation in developing countries are relatively new. In this study, the intention of students to adopt online cash waqf was predicted for the first time by considering their knowledge of cash waqf and their trust in online cash waqf transactions.

The aim of this study is to optimize the electrospinning parameters used in the production process of polyvinyl chloride (PVC) nanofibers.

The response surface methodology (RSM) was used to determine the experimental design. The 30 nanofiber prototypes candidates were electrospun using a needle-based electrospinning machine. PVC polymer, N-dimethyl formamide and tetrahydrofuran solvents were used to prepare the electrospinning solution.

The electrospun nanofibers had a mean diameter of 386 ± 136.57 nm, in the range of 200−412 nm. The mean porosity was 31.60 ± 6.37% in the range of 15.33−41.53%. The webs made from electrospun nanofibers had a mean pressure loss of 194.23 ± 47.7 pa in the range of 124−300 pa. The highest statistically significant correlation was observed between solution concentration and nanofiber diameter (r = 0.756, p < 0.05).

The optimal electrospinning parameters were determined to be: a solution concentration of 11 weight percent, a voltage of 16.5 kV, a needle-collector distance of 13.5 cm and an electrospinning duration of 4 h.