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This paper aims to examine the impact of the assurance and advisory role of internal audit (ADRIA) on organisational, human and technical proactive measures to enhance cybersecurity (CS).

The questionnaire was used to collect data for 97 internal auditors (IAu) from the Gulf Cooperation Council countries. The authors used partial least squares (PLS) to test the hypotheses.

The results show a positive effect of the ADRIA on each of the organisational proactive measures, human proactive measures and technical proactive measures to enhance CS. The study also found a positive effect of the confirmatory role of IA on both human proactive measures and technical proactive measures to enhance CS. No effect of the confirmatory role of IA on the organisational proactive measures is found.

This study focused on only three proactive measures to enhance CS, and this study was limited to the opinions of IAu. In addition, the study was limited to using regression analysis according to the PLS method.

The results of this study show that managers need to consider the influential role of IA as a value-adding activity in reducing CS risks and activating proactive measures. Also, IAu must expand its capabilities, skills and knowledge in CS auditing to provide a bold view of cyber threats. At the same time, the institutions responsible for preparing IA standards should develop standards and guidelines that help IAu to play assurance and advisory roles.

To the best of the authors’ knowledge, this is the first study of its kind that deals with the impact of the assurance and ADRIA on proactive measures to enhance CS. In addition, the study determines the nature of the advisory role and the assurance role of IA to strengthen CS.

The objective of this study was to delineate and compare enteral nutrition (EN) practices among neonatal units across the Arabian Gulf countries.

A cross-sectional study was conducted by recruiting 255 clinicians working in neonatal units in the Arabian Gulf countries.

Out of 255 invited clinicians, 73 (29%) participated in the survey. Neonatal units used varied EN strategies, where feeding practices exhibited variability. The majority (74%) of units had a local standard feeding protocol, while 18% followed international protocols, and 8% did not adhere to a specific protocol. When maternal milk was not used, the main alternatives were preterm formula (67%) and predigested formula (14%). The age at which the first EN was commenced and the reported advancement rate showed significant variations among different units (p < 0.001). The initiation of fortification was primarily driven by reaching a specific enteral volume (commonly reported as 100 mL/kg/day) and addressing poor postnatal growth. Fortification practices did not differ significantly among professions, except for the initial fortification strength, where none of the dietitians and only 8.3% of neonatologists preferred full strength, compared to 28.6% and 21.4% of medical residents and nurses, respectively (p = 0.033).

This study marks the first exploration of EN practices in neonatal units, examining their local and cross-country variations. It provides valuable insights to guide local trials and foster global collaboration among neonatal units to establish a unified knowledge base, standardized practices and promote research and innovation, ultimately contributing to optimal feeding practices for very preterm infants.

This study evaluated the impact of a faculty training program on student assessment using the Kirkpatrick model.

A self-reported survey assessed 111 Saudi and non-Saudi participants' satisfaction. Subjective and objective measures (self-reported measures, assessment literacy inventory and performance-based assessment tasks) gauged participants' learning level. Pre- and post-training data were collected from 2020 to 2022.

A highly significant effect on satisfaction (>80%) and learning levels was observed, as manifested by workplace practices of student assessment (>70%, the cut-off score). Pre- and post-training comparisons of participants' satisfaction and assessment literacy scores showed significant improvements following training. Multiple regression analyses showed no significant effects for gender and educational attainment but a substantial impact of academic cluster on participants' student assessment skills.

Long-term effects of training faculty on assessment practices and student achievement will be studied at the institutional level in future research.

The current study contributes to human capital investment via faculty training on student assessment, helping them comply with assessment best practices. This assures the quality, fairness and consistency of assessment processes across disciplines in higher education institutions, enhances assessment validity and trust in educational services and may support institutional accreditation.

This study provides opportunities for sharing best practices and helps establish a community of practice. It enhances learning outcomes achievement and empowers higher education graduates with attributes necessary to succeed in the labor market. The human capital investment may have a long-term impact on overall higher education quality.

This study contributes to the scarce literature investigating the impact of training faculty from different clusters on student assessment using subjective and objective measures. It provides developing and evaluating a long-term student assessment program following the Kirkpatrick model.

The current analysis produces the fractional sample of non-Newtonian Casson and Williamson boundary layer flow considering the heat flux and the slip velocity. An extended sheet with a nonuniform thickness causes the steady boundary layer flow’s temperature and velocity fields. Our purpose in this research is to use Akbari Ganji method (AGM) to solve equations and compare the accuracy of this method with the spectral collocation method.

The trial polynomials that will be utilized to carry out the AGM are then used to solve the nonlinear governing system of the PDEs, which has been transformed into a nonlinear collection of linked ODEs.

The profile of temperature and dimensionless velocity for different parameters were displayed graphically. Also, the effect of two different parameters simultaneously on the temperature is displayed in three dimensions. The results demonstrate that the skin-friction coefficient rises with growing magnetic numbers, whereas the Casson and the local Williamson parameters show reverse manners.

Moreover, the usefulness and precision of the presented approach are pleasing, as can be seen by comparing the results with previous research. Also, the calculated solutions utilizing the provided procedure were physically sufficient and precise.

Misunderstanding and harmful stereotyping have become commonplace amongst people in the United States and the Middle East/North Africa (MENA) region since 2001, if not earlier. If universities are the locus of transformative education, work remains towards remedying these issues.One non-profit organisation, “Natafaham (pseudonym, Arabic for « we understand each other”), works to undo this negativity student by student. It brings participants from the MENA and Europe/North America into dialogue via Zoom each week. The inter-cultural dialogue availed to participants is empowering to actors, including the dialogue facilitator. This narrative is an autoethnographic exploration of my experience as an intercultural dialogue facilitator. Yet reviewing contemporaneous notes and reflections revealed structural aspects of this programme that empower voices from the MENA region, while facilitating learning amongst participants on both sides of the Atlantic. Such aspects include the format and the location of the programme, its focus on individuals rather than institutions or groups, its mixed top-down and bottom-up approach, and the opportunities it avails for ascension to positions of authority. This narrative analyses these aspects through several lenses and academic traditions, including those of global citizenship, critical internationalisation, (reciprocal) global service learning, and socio-cultural frameworks of second language acquisition. The chapter urges that these aspects are recognised as key catalysts of (more) equal relationships between youth in the MENA region and the United States, which merit widespread replication. It concludes by envisioning a still more equal relationship predicated upon more equitable language usage.

This study aims to examine the relationship between corporate social responsibility (CSR) award and sustainability assurance levels for the French CAC 40 companies.

A sample of 57 French companies in the CAC 40 index corresponding to 448 observations was analyzed between 2008 and 2020 using an ordinal regression.

The main results conclude that the inclusion in the Dow Jones Sustainability Index World, the CSR award and the introduction of the Grenelle 2 law have a significant influence on sustainability assurance levels. However, incentive compensation does not appear to be relevant to explain sustainability assurance levels.

The present study focuses on a sample, limited to companies belonging to the CAC 40 index. To enhance the understanding of sustainability assurance levels, this research may include other global sustainability indices, such as the MSCI World and the FTSE4Good World, in the CSR awards.

This study could be useful for audit practitioners, leading them to reconsider their evaluation methods and take into account CSR incentives for a more objective analysis. Regulators should investigate the current CSR issues to improve CSR disclosure standards. Finally, these findings could motivate other researchers to expand the scope of the research to diverse contexts.

This study helps fill the gap existing in sustainability assurance literature by highlighting the relationship between CSR rewards and sustainability assurance levels.

This study aims to obtain methods to identify and find the place of damage, which is one of the topics that has always been discussed in structural engineering. The cost of repairing and rehabilitating massive bridges and buildings is very high, highlighting the need to monitor the structures continuously. One way to track the structure's health is to check the cracks in the concrete. Meanwhile, the current methods of concrete crack detection have complex and heavy calculations.

This paper presents a new lightweight architecture based on deep learning for crack classification in concrete structures. The proposed architecture was identified and classified in less time and with higher accuracy than other traditional and valid architectures in crack detection. This paper used a standard dataset to detect two-class and multi-class cracks.

Results show that two images were recognized with 99.53% accuracy based on the proposed method, and multi-class images were classified with 91% accuracy. The low execution time of the proposed architecture compared to other valid architectures in deep learning on the same hardware platform. The use of Adam's optimizer in this research had better performance than other optimizers.

This paper presents a framework based on a lightweight convolutional neural network for nondestructive monitoring of structural health to optimize the calculation costs and reduce execution time in processing.

This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.

This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.

The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.

This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.

Amidst the stressful work environment in the healthcare sector, employees struggle to maintain prosocial behavior and work reattachment. The potential role of awe and mindfulness in addressing these issues remains unexplored. This study investigates how coworker prosocial behavior affects work reattachment while considering the mediating role of mindfulness and the moderating role of awe.

Using a quantitative research design, data were collected through a survey questionnaire from 356 healthcare professionals in Pakistan. The data were analyzed in SPSS and AMOS for reliability and validity statistics, as well as for hypothesis testing.

The findings revealed a significant link between coworker prosocial behavior and work reattachment. Mindfulness acted as a mediator between coworker prosocial behavior and work reattachment, while awe had a positive moderating effect on these relationships.

The findings emphasize the need for fostering these elements to manage stress, support employees and improve work reattachment.

The existing literature lacks empirical evidence regarding the impact of coworker prosocial behavior on employee outcomes, and this study contributes by examining the roles of awe and mindfulness in the healthcare sector.

This study aims to analyze the two-dimensional ferrofluid flow in porous media. The effects of changes in parameters such as permeability parameter, buoyancy parameter, Reynolds and Prandtl numbers, radiation parameter, velocity slip parameter, energy dissipation parameter and viscosity parameter on the velocity and temperature profile are displayed numerically and graphically.

By using simplification, nonlinear differential equations are converted into ordinary nonlinear equations. Modeling is done in the Cartesian coordinate system. The finite element method (FEM) and the Akbari-Ganji method (AGM) are used to solve the present problem. The finite element model determines each parameter’s effect on the fluid’s velocity and temperature.

The results show that if the viscosity parameter increases, the temperature of the fluid increases, but the velocity of the fluid decreases. As can be seen in the figures, by increasing the permeability parameter, a reduction in velocity and an enhancement in fluid temperature are observed. When the Reynolds number increases, an increase in fluid velocity and temperature is observed. If the speed slip parameter increases, the speed decreases, and as the energy dissipation parameter increases, the temperature also increases.

When considering factors like thermal conductivity and variable viscosity in this context, they can significantly impact velocity slippage conditions. The primary objective of the present study is to assess the influence of thermal conductivity parameters and variable viscosity within a porous medium on ferrofluid behavior. This particular flow configuration is chosen due to the essential role of ferrofluids and their extensive use in engineering, industry and medicine.