Improving food safety compliance of potential employees through a novel model of knowledge, attitude, commitment, and practice.

The global burden of foodborne illnesses remains high due to consumption of contaminated food. Vigilant attention from all, particularly food handlers, is needed to address food safety concerns and minimize the risks that affect consumer health, international business, and tourism worldwide. The main objectives of this study were to: (i) evaluate the food safety knowledge, attitudes, commitment (involving affective, continuance, and normative types), and practices of students studying subjects related to food sciences in Jordanian universities and (ii) examine the impact of knowledge and attitude on commitment, and subsequently, on relevant practices using structural equation modeling.

1 Million Segmented Red Blood Cells With 240 K Classified in 9 Shapes and 47 K Patches of 25 Manual Blood Smears.

Around 20% of complete blood count samples necessitate visual review using light microscopes or digital pathology scanners. There is currently no technological alternative to the visual examination of red blood cells (RBCs) morphology/shapes. True/non-artifact teardrop-shaped RBCs and schistocytes/fragmented RBCs are commonly associated with serious medical conditions that could be fatal, increased ovalocytes are associated with almost all types of anemias.

Typical and extreme weather datasets for studying the resilience of buildings to climate change and heatwaves.

We present unprecedented datasets of current and future projected weather files for building simulations in 15 major cities distributed across 10 climate zones worldwide. The datasets include ambient air temperature, relative humidity, atmospheric pressure, direct and diffuse solar irradiance, and wind speed at hourly resolution, which are essential climate elements needed to undertake building simulations. The datasets contain typical and extreme weather years in the EnergyPlus weather file (EPW) format and multiyear projections in comma-separated value (CSV) format for three periods: historical (2001-2020), future mid-term (2041-2060), and future long-term (2081-2100).

Factors affecting metaverse adoption in education: A systematic review, adoption framework, and future research agenda.

The Metaverse, underpinned by its technical infrastructure, heavily relies on user engagement and behavior for successful integration into educational settings. Understanding its driving factors is essential for such a platform to transition from theory to practice, especially in educational settings. However, these factors remain elusive due to inconsistencies in infrastructure and environments.

Enhancing inclusive education in the UAE: Integrating AI for diverse learning needs.

Introduction: Artificial Intelligence (AI) mediated systems have become important in educational set-ups, and it is still debatable whether or not they can be useful in special needs education. This qualitative research scrutinizes the experiences and perceptions of exceptional learners, as an example of special needs education, engaged in AI-mediated discussions versus traditional classroom dialogues. The study aims to reveal how these learners process and construct knowledge differently when AI is incorporated into their discussions and how it compares to conventional learning environments.

Towards a dialogical and progressive educational policy framework: Manoeuvring a middle way among the polarised constructs.

Policy science and practice around the world, including educational policies, are dominated by popular, extreme approaches such as market-orientated approaches at one end and critical argumentative approaches at the other end. This study therefore aims to manoeuvre a middle way to propose a dialogical and progressive educational policy framework and explores the research question: 'how could a middle way (a dialogical and progressive framework) be manoeuvred among the polarised policy constructs?' The study embraces Lynham's five phases of theory building as the basis for this research, which includes conceptual development, operationalisation, confirmation/disconfirmation, application, and continuous refinement. The study explores some of the known existing policy frameworks for conceptual mapping, investigates the underlying dynamics and discourses to operationalise, uses diverse arguments in the literature to confirm/disconfirm and proposes to mark the emerging patterns, trends, and gaps in policy research to apply and refine.

Determinants of cloud computing integration and its impact on sustainable performance in SMEs: An empirical investigation using the SEM-ANN approach.

Although extant literature has thoroughly investigated the incorporation of cloud computing services, examining their influence on sustainable performance, particularly at the organizational level, is insufficient. Consequently, the present research aims to assess the factors that impact the integration of cloud computing within small and medium-sized enterprises (SMEs) and its subsequent effects on environmental, financial, and social performance. The data were collected from 415 SMEs and were analyzed using a hybrid SEM-ANN approach.

Improving video surveillance systems in banks using deep learning techniques.

In the contemporary world, security and safety are significant concerns for any country that wants to succeed in tourism, attracting investors, and economics. Manually, guards monitoring 24/7 for robberies or crimes becomes an exhaustive task, and real-time response is essential and helpful for preventing armed robberies at banks, casinos, houses, and ATMs. This paper presents a study based on real-time object detection systems for weapons auto-detection in video surveillance systems.

The psychological impact of COVID-19 on healthcare work force in the Middle East region C-S study.

Introduction: COVID-19, is one of the biggest challenges facing humanity in the 21st century (1). The pandemic outbreak as affected all human activities, starting with healthcare and medical service passing with economy and social relationships, as well as political, religious and cultural enactments (2). The healthcare workers were the most affected fighting in the frontline working longer hours under a high risk of being infected (3).

Genuine policy learning is fundamental: the journey of the United Arab Emirates toward the establishment of health technology assessment.

The launch of innovative technologies has been credited with significant improvements in health indicators, but it comes at a high financial impact, and the value of certain innovations may not be well documented. Health technology assessment (HTA) is a universally established process to assess the incremental value of innovations. Despite its acknowledged value, almost one-third of the countries around the globe have not established yet a formal HTA in their health systems.

LDDNet: A Deep Learning Framework for the Diagnosis of Infectious Lung Diseases.

This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-ray (CXR) images. This framework is termed optimized DenseNet201 for lung diseases (LDDNet). The proposed LDDNet was developed using additional layers of 2D global average pooling, dense and dropout layers, and batch normalization to the base DenseNet201 model.

Hospital selection framework for remote MCD patients based on fuzzy q-rung orthopair environment.

This research proposes a novel mobile health-based hospital selection framework for remote patients with multi-chronic diseases based on wearable body medical sensors that use the Internet of Things. The proposed framework uses two powerful multi-criteria decision-making (MCDM) methods, namely fuzzy-weighted zero-inconsistency and fuzzy decision by opinion score method for criteria weighting and hospital ranking. The development of both methods is based on a Q-rung orthopair fuzzy environment to address the uncertainty issues associated with the case study in this research.

Organizational culture and affective commitment to e-learning' changes during COVID-19 pandemic: The underlying effects of readiness for change.

Higher education institutions (HEIs) have been embracing digital transformation for years, but the disruptive influence of the global COVID-19 pandemic has accelerated it. Despite the importance of organizational culture (OC) for the successful delivery of e-learning, empirical studies looking at its impact on academics' readiness and affective commitment to e-learning-induced changes are scant. This study unveils the underlying impacts of multiple employee readiness for change (ERFC) dimensions in the OC-employee affective commitment to change (EACC) relationship.

The Interplay of E-commerce, Resilience and Exports in the Context of COVID-19.

Scholars have extolled e-commerce as a pathway for sustaining firm operations in the unique circumstances of COVID-19. To add crisis time evidence to the body of work, and based on World Bank Enterprise Survey data, this inquiry interrogates 249 small manufacturing firms in Italy by examining the effect of e-commerce on (1) resilience, (2) direct exports and (3) indirect exports. The results show that while e-commerce has a positive impact on direct exports, a negative influence is recorded on indirect exports.

Toward automatic motivator selection for autism behavior intervention therapy.

Children with autism spectrum disorder (ASD) usually show little interest in academic activities and may display disruptive behavior when presented with assignments. Research indicates that incorporating motivational variables during interventions results in improvements in behavior and academic performance. However, the impact of such motivational variables varies between children.

Correction: Organizational Resilience of Higher Education Institutions: An Empirical Study during Covid-19 Pandemic.

[This corrects the article DOI: 10.1057/s41307-022-00272-2.].

Novel dynamic fuzzy Decision-Making framework for COVID-19 vaccine dose recipients.

Introduction: The vaccine distribution for the COVID-19 is a multicriteria decision-making (MCDM) problem based on three issues, namely, identification of different distribution criteria, importance criteria and data variation. Thus, the Pythagorean fuzzy decision by opinion score method (PFDOSM) for prioritising vaccine recipients is the correct approach because it utilises the most powerful MCDM ranking method. However, PFDOSM weighs the criteria values of each alternative implicitly, which is limited to explicitly weighting each criterion.

What Has Been the Impact of COVID-19 on Digitalization, Innovation and Crisis Management of Higher Education and Quality Assurance?-A Taiwan Case Study in Alignment with the INQAAHE Virtual Review.

The impact of COVID-19 on higher education and quality assurance (QA) has already elicited global attention and discussion. QA agencies and networks quickly learned to adapt in order to carry out assessments, accreditations, recognitions, and reviews in a full virtual mode. These practices include using shared folders for virtual desk review, video conferencing platforms for interviews, and virtual site visits.

Medical data integration using HL7 standards for patient's early identification.

Integration between information systems is critical, especially in the healthcare domain, since interoperability requirements are related to patients' data confidentiality, safety, and satisfaction. The goal of this study is to propose a solution based on the integration between queue management solution (QMS) and the electronic medical records (EMR), using Health Level Seven (HL7) protocols and Extensible Markup Language (XML). The proposed solution facilitates the patient's self-check-in within a healthcare organization in UAE.

Post award arbitral tribunal's mandate under the UNCITRAL Model Law and national laws based thereon.

The UNCITRAL Model Law on International Commercial Arbitration provides for the extension of the mandate of the arbitral tribunal post issuance of the final award for the issuance of correction, interpretation, additional award, and remittance of the award back to the arbitral tribunal to remove grounds for challenging the award. Using a doctrinal approach, this paper examines the deviations of the national laws of adopting jurisdictions from the Model Law in regards to this extended mandate, and evaluates the improvements and drawbacks in these deviations. Mainly, the findings of this paper are that, of the many deviations, the positive changes are those that provide comfortable and lenient default provisions for the benefit of inexperienced parties, and since correction, interpretation, additional award, and remittance are useful provisions that are designed to help self-rectify the arbitral process, without adversely delaying it, then the changes that increase the efficacy of these provisions are welcomed.

Facilitating ESCO market development through value co-creation: role of utility sector intermediaries.

The growth of energy service company (ESCO) markets in the private sector is restricted by a fragmented and highly uncertain market and by customers who are often unknowledgeable and unwilling. This study explores the potential role of utility companies as intermediaries in connecting supply-side ESCOs with potential demand-side customers in a manner that ensures customer satisfaction. The paper adopts a customer-centric, service-dominant logic perspective to examine how a utility company facilitates value co-creation in an in-depth case study of an extensive retrofit programme in the Emirate of Sharjah, United Arab Emirates.

User Acceptance Level of and Attitudes towards Telemedicine in the United Arab Emirates: A quantitative study.

Objectives: This study aimed to examine acceptance levels of and attitudes towards telemedicine among users in the United Arab Emirates (UAE) and assess associations between perceived usefulness (PU), perceived ease of use (PEOU), attitudes towards use (ATU) and behavioural intention of use (BIU) in relation to telemedicine technology.

Methods: This cross-sectional study used a simple random sampling design to obtain an appropriate sample from throughout the UAE. The technology acceptance model (TAM) and Rogers' diffusion of innovations (DOI) theory were applied as the conceptual basis for this study.