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Purpose: The main objective of the research is to examine the influence of audit committee attributes on the integrated reporting quality (IRQ) and to investigate whether this association is moderated by board gender diversity in the manufacturing and non-manufacturing sectors. The study specifically investigates the association between audit committee independence, meetings frequency, financial expertise, audit committee size, and integrated reporting quality. Design/methodology/approach: The data collection was from the financial statements and corporate governance reports of 54 Egyptian firms listed on the stock market [EGX100] for the period of 2018–2022. The study used pooled effect modelling and performed data analysis using the STATA software. Findings: For the manufacturing sector, the results showed a significant impact of audit committee independence and meetings frequency on IRQ, while audit committee size and financial expertise showed insignificant association with IRQ. Board gender diversity moderates the association between audit committee meetings only and IRQ. In contrast, audit committee financial expertise and meetings frequency significantly impact IRQ, while audit committee independence and size showed an insignificant impact on IRQ in the non-manufacturing sector. Also, board gender diversity moderates the association between audit committee and IRQ. The findings highlight the significance of AC attributes and provide guidance to firms to strengthen their audit committees in order to provide high quality of integrated reports to increase investor trust in the Egyptian business environment as it is now mandatory by the government. Originality/value: This research offers unique perspectives on the association between variables in Egypt. This study is one of the first investigations on the impact of audit committee attributes and board diversity on integrated reporting quality within the context of Egyptian listed companies. Comprehending the ways in which audit committee attributes impact the integrated reporting quality in the manufacturing and non-manufacturing sectors can enable organizations to devise focused approaches that comply to the unique operational, regulatory, and investor demands in each sector. [ABSTRACT FROM AUTHOR]

Since money laundering has developed rapidly and has different methods depending on time and place, it is no doubt one of the most important and dangerous legal problems facing legislators. Consequently, finding in many developing countries have problems related to the organization of laws that can overcome its ability to weaken the local economy. When the researcher reviewed the legislation under the current study (Egyptian, Jordanian, Emirati, and Iraqi), he found that there are instances of deficiency and weak ability to confront traditional money laundering crime, let alone a new form of money laundering crime represented in the digital world. Therefore, the researcher’s interest was focused on studying the four most important countries in which there are money laundering crimes and trying to shed light on the legal problems to confront it. The current study deals with the legislative treatment of money laundering crime through electronic means by examining four Arab legislations. The results of the study showed the shortcomings of the legislation under study in their treatment of money laundering by defining it, discussing its characteristics, and ways to combat and get rid of it. [ABSTRACT FROM AUTHOR]

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with 213 eyes examined in Iraq and obtained AUCs of 0.91–0.92 and an accuracy range of 88–92%. The proposed model is a step toward improving the detection of clinical and subclinical forms of KCN. [ABSTRACT FROM AUTHOR]