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This paper aims to provide insights into the complicated relationship between earnings management (EM) and corporate social responsibility (CSR) during the financial downturn caused by the COVID-19 pandemic.

Parametric t-tests and non-parametric Wilcoxon rank-sum tests accompanied by ordinary least squares regression analysis, augmented with Newey–West procedure approaches, are used for a sample that consists of 1,984 firms from 47 countries for the period of 2014–2020. EM was proxied once with discretionary accruals using the modified Jones model (1995) and once with real earnings management (REM) using the Roychowdhury model (2006). This study uses environmental, social, and governance scores from the Thomson Reuters database as a proxy for CSR.

The results reveal that firms tend to engage more in EM practices during the pandemic and that more socially responsible firms tend to be honest and transparent during the financial reporting process. Interestingly, it was found that more socially responsible firms engaged less in REM practices during the pandemic.

The findings of this research help lenders, investors, policymakers and managers gain a better understanding of EM practices during a negative shock and shed light on the importance of CSR in being ethical.

The findings extend both the literature on the role of CSR in promoting financial reporting quality and the literature on the impact of COVID-19 on accrual and REM practices.

This paper is based on a study which examined the current training evaluation activity and challenges that face Kuwaiti organisations. The study sample was five UK organisations (recognised as best practice organisations in their T&D activities) and 77 Kuwaiti organisations (40 government and 37 private). Interviews and questionnaires were used. The study reveals that the majority of respondents, both in government and in private sectors, only evaluate their training programme occasionally. The most popular evaluation tools and technique used by government and private sectors were questionnaires. The most common model used by Kuwaiti organisations is the Kirkpatrick model, while the most common level of evaluation for both government and private sector is reaction type.

Given the increased importance of food in tourists’ travel experience, the purpose of this paper is to explore the current and future potential of local food and foodways in marketing Egyptian destinations online.

The content of 20 Egyptian destination marketing organization (DMO) websites was subject to a content analysis. A checklist was developed based on literature analysis. The frequencies of information related to food culture and cuisine marketing were tallied, followed by a qualitative assessment of contents from the various websites. The results were further discussed with DMO representatives to provide contextualized insights as to the future potential of utilizing local food and food tourism initiatives as a component of DMOs website marketing in Egypt.

The study noted some initial efforts for Egyptian DMO websites to market food culture and gastronomic practices; however, the results suggest that the usage of food culture on Egyptian DMOs websites is still in its infancy. The study also highlights the challenges that need to be tackled as well as the resources required for food tourism development.

This study illustrates the need and potential capacity of Egyptian DMO websites to market food culture and local cuisines (including traditional foods and table manners). These results are expected to help Egyptian DMOs to strategically embrace local cuisine and food culture as a vehicle for destination marketing.

This case study provides insights for African and other developing economies in their destination marketing. The proposed framework and guidelines are intended to potentially serve as a framework for destination marketers and entrepreneurs to optimize the tourism potential of food culture.

The aim of this research is to examine the relationship between green supply chain management and sustainability performance in a manufacturing context.

A survey approach was adopted to collect data from 163 manufacturing organizations to test the research hypotheses. A structural equation modeling (SEM) using the technique of path analysis with bootstrapping is used to test the hypothesized relationships.

The research findings provide supporting evidence for the importance of implementing green supply chain management (GSCM) as a holistic system that includes internal and external green practices. Besides, the findings highlight the direct effect of GSCM on environmental, social and operational performance. Finally, the findings provide supporting evidence that GSCM could only be translated into better economic returns through the improvement of environmental and operational performance.

The nature of the surveyed sample and the use of a single informant might limit the ability to generalize the research findings outside the research context.

The research findings help managers understand that GSCM must be implemented as a holistic system and that the real benefits of its implementation extend beyond the mere environmental benefits to include operational, social as well as economic benefits.

The paper’s contribution to knowledge is twofold. First, the study identifies how GSCM is conceptualized and how its effect is translated into improved economic performance. Second, the research explains the contradicting findings in previous studies regarding the relationship between GSCM and economic performance.

The study proposed a human–robot interaction (HRI) framework to enable operators to communicate remotely with robots in a simple and intuitive way. The study focused on the situation when operators with no programming skills have to accomplish teleoperated tasks dealing with randomly localized different-sized objects in an unstructured environment. The purpose of this study is to reduce stress on operators, increase accuracy and reduce the time of task accomplishment. The special application of the proposed system is in the radioactive isotope production factories. The following approach combined the reactivity of the operator’s direct control with the powerful tools of vision-based object classification and localization.

Perceptive real-time gesture control predicated on a Kinect sensor is formulated by information fusion between human intuitiveness and an augmented reality-based vision algorithm. Objects are localized using a developed feature-based vision algorithm, where the homography is estimated and Perspective-n-Point problem is solved. The 3D object position and orientation are stored in the robot end-effector memory for the last mission adjusting and waiting for a gesture control signal to autonomously pick/place an object. Object classification process is done using a one-shot Siamese neural network (NN) to train a proposed deep NN; other well-known models are also used in a comparison. The system was contextualized in one of the nuclear industry applications: radioactive isotope production and its validation were performed through a user study where 10 participants of different backgrounds are involved.

The system was contextualized in one of the nuclear industry applications: radioactive isotope production and its validation were performed through a user study where 10 participants of different backgrounds are involved. The results revealed the effectiveness of the proposed teleoperation system and demonstrate its potential for use by robotics non-experienced users to effectively accomplish remote robot tasks.

The proposed system reduces risk and increases level of safety when applied in hazardous environment such as the nuclear one.

The contribution and uniqueness of the presented study are represented in the development of a well-integrated HRI system that can tackle the four aforementioned circumstances in an effective and user-friendly way. High operator–robot reactivity is kept by using the direct control method, while a lot of cognitive stress is removed using elective/flapped autonomous mode to manipulate randomly localized different configuration objects. This necessitates building an effective deep learning algorithm (in comparison to well-known methods) to recognize objects in different conditions: illumination levels, shadows and different postures.

In the present paper, the new concept of “memory dependent derivative” in the Pennes’ bioheat transfer and heat-induced mechanical response in human living tissue with variable thermal conductivity and rheological properties of the volume is considered.

A problem of cancerous layered with arbitrary thickness is considered and solved analytically by Kirchhoff and Laplace transformation. The analytical expressions for temperature, displacement and stress are obtained in the Laplace transform domain. The inversion technique for Laplace transforms is carried out using a numerical technique based on Fourier series expansions.

Comparisons are made with the results anticipated through the coupled and generalized theories. The influence of variable thermal, volume materials properties and time-delay parameters for all the regarded fields for different forms of kernel functions is examined.

The results indicate that the thermal conductivity and volume relaxation parameters and MDD parameter play a major role in all considered distributions. This dissertation is an attempt to provide a theoretical thermo-viscoelastic structure to help researchers understand the complex thermo-mechanical processes present in thermal therapies.

Several new methylsulfanylpyrazolopyrimidines and methylsulfanylpyrazolotriazine derivatives containing an arylazo function were obtained. The application and characteristics for the synthesised dyes are demonstrated.

The purpose of this paper is to study the effect of gamma-rays on murexide (Mx) dye and its possible use as radiation dosimeters in two different dosimetry systems. The first system depends on the Mx dye as a liquid dosimeter. The second dosimetry system depends also on the same dye but as in a gel form, which is more sensitive to gamma-rays.

The prepared Mx (solutions/gels) have a considerable two peaks at 324 and 521 nm that upon irradiation, the intensity of these peaks decreases with the increasing radiation dose.

The gamma-ray absorbed dose for these dosimeters was found to be up to 2 kGy for the solution samples and 40 Gy for the gels. Radiation chemical yield, dose response function, radiation sensitivity and before and after-irradiation stability under various conditions were discussed and studied.

It is expected that the radiolysis of the Mx dye can be used as radiation dosimeters in two different dosimetry systems; liquid and gel dosimeters. This can be applied in a wide range of gamma radiation practical industrial applications in water treatment, food irradiation dosimeters, radiotherapy and fresh food irradiation and seed production.

Both of the prepared Mx dyes, either as solutions or gel samples, can be facilely prepared from commercially, cheap, safe, available chemicals and suitable for useful applied Mx solutions and gels radiation dosimeters.

The purpose of this paper is to present a review on the use of the recall metric for evaluating information retrieval systems, especially search engines.

This paper investigates different researchers’ views about recall metrics.

Five different definitions for recall were identified. For the first group, recall refers to completeness, but it does not specify where all the relevant documents are located. For the second group, recall refers to retrieving all the relevant documents from the collection. However, it seems that the term “collection” is ambiguous. For the third group (first approach), collection means the index of search engines and, for the fourth group (second approach), collection refers to the Web. For the fifth group (third approach), ranking of the retrieved documents should also be accounted for in calculating recall.

It can be said that in the first, second and third approaches, the components of the retrieval algorithm, the retrieval algorithm and crawler, and the retrieval algorithm and crawler and ranker, respectively, are evaluated. To determine the effectiveness of search engines for the use of users, it is better to use the third approach in recall measurement.

The value of this paper is to collect, identify and analyse literature that is used in recall. In addition, different views of researchers about recall are identified.

Najib Mahfuz is the first Arab‐language author to win the Nobel Prize in literature. Born in 1911 the son of a middle‐class Jamaliyah merchant, he became the most popular novelist in Egypt and the Arab countries.