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The purpose of this study is to analyze the fluctuations in gold prices within the Saudi Arabian market and to develop a reliable forecasting model to aid market participants and policymakers in making informed decisions.

In this study, we employ a rigorous time series analysis methodology, including the ARIMA (Auto Regressive Integrated Moving Average) model, to analyze historical gold price data in the Saudi Arabian market. The approach involves identifying optimal model parameters and assessing forecast accuracy to provide actionable insights for market participants.

The study showcases that the autoregressive properties of past gold prices play a pivotal role in capturing the inherent serial correlation within the market, enabling the ARIMA model to effectively forecast future gold price movements with accuracy.

Our study primarily focuses on quantitative analysis, whereas few qualitative parameters are not included. Future studies may benefit from incorporating qualitative factors and expert opinions to enhance the robustness of gold price predictions and capture the full spectrum of market dynamics.

Participants and policymakers may find this study helpful in navigating the complicated Saudi Arabian gold market. By understanding financial stability and investment decisions more thoroughly, individuals and institutions may be able to manage their portfolios more effectively.

By combining historical insights with advanced ARIMA modeling techniques, this research provides valuable insight into gold price dynamics in the Saudi Arabian market.

Purpose: Industry 5.0 is a revolution building on the fourth industrial revolution, adopting human-centred production. It aims for a future that enables people to live with high welfare power by combining the power of the technologies it supports and uses with human creativity and skill. The study explores how Industry 5.0 differs from the industrial revolutions that preceded it, highlighting the challenges, benefits, and possible future trends of Industry 5.0 systems.

Need for the study: Industry 5.0 differs from Industry 4.0 – it represents a human-centred and sustainable approach along with the innovations it brings. Examination of the still emerging concept of Industry 5.0 and to investigate the driving forces behind the emergence is needed.

Methodology: The characteristics that distinguish the Industry 5.0 system from the fourth industrial revolution are explored in detail. The areas in which the technologies used in Industry 5.0 provide benefits and the challenges in implementing the system are analysed. The measures to be taken to overcome these difficulties and the deficiencies were investigated.

Findings: The most important principle of Industry 5.0 is human-centred production and technology. In addition, sustainability, personalised production, new business opportunities, more environmentally friendly and renewable energy use, and bioeconomy are shown as innovations brought by Industry 5.0.

Practical implications: The adoption of Industry 5.0 appears to be a mandatory change. In addition, the study emphasises the measures that businesses should take in terms of sustainability, sustainable economy, the importance of the use of renewable energy sources, and much more environmentally friendly and waste-free production.

This study aims to understand and analyze the aspects influencing students’ attitudes and behavior toward the use of metaverse in education. The metaverse is currently viewed as technology with immense prospects. However, the practice of the metaverse for educational motives is rarely deliberated.

To assess the effect of the metaverse on students' knowledge and use of resources, general interests and attitudes toward the metaverse in education, a survey was conducted. The collected data were analyzed using a confirmatory factor analysis (CFA) in the first phase to address the various validity parameters. In the second phase, path analysis of the model was performed using structural equation modeling (SEM).

The study investigated how students intended to behave while using the metaverse for learning. The attitude toward adopting metaverse as technology is influenced by perceived utility and simplicity of use. This leads to behavioral intention as well. Studies reveal that the aspect of perceived usefulness is considered to be more significant in assessing the intention of use.

This quantitative study contributes to the literature on metaverse, which is in the growing stage. In the educational sector, the existing studies are scarce; hence, the addition to the literature on metaverse is quite significant in the education domain.

The study benefits the students and the academicians because metaverse is largely considered an integral part of technology platforms, which has to be included in the learning systems eventually. There are few courses where the use of metaverse is already initiated at an introductory level, thus opening a broad spectrum of opportunities at all levels. It can provide scholars access to a massive array of resources, including multimedia presentations, interactive objects that support the delivery of lessons, videos, images and audio recordings.

This study adds to the existing literature by examining the impact of metaverse in education. The research focused on the students pursuing higher education who were mostly aware of metaverse and were open to the idea of learning and understanding through technology inclusion.

Purpose: To investigate the key technologies facilitating the transition towards Industry 5.0 and analysing the contributions of Nvidia, a prominent leader in this field, to these technological advancements.

Significance of the study: Technology companies such as Nvidia play a critical role in this transformation through their innovative solutions. This study addresses the need to understand this evolving landscape and the significant impact of the Nvidia.

Methodology: This study is a qualitative approach that examines the existing literature and secondary case studies pertaining to Industry 5.0, and Nvidia. This study examines Nvidia’s high-performance graphics processing units (GPUs), the digital twin platform Omniverse, and the humanoid robot technology development platform, Isaac.

Findings: The next generation of GPUs with the Blackwell architecture is expected to further advance the development of large language models. The Nvidia Omniverse platform contributes significantly to the development of digital twins, a crucial technology for Industry 5.0. The Nvidia Isaac platform focuses on the development of humanoid robot technology, which is a key component of Industry 5.0. Utilizing realistic simulations with Isaac Sim, imitating human behavior with GR00T, and leveraging the high-performance processing power of Jetson Thor, the platform facilitates the creation of robots capable of safe and effective human–robot collaboration. Nvidia has emerged as a leader in the artificial intelligence (AI), robotics, and gaming sectors because of its innovative and agile company culture.

Practical implications: Companies can leverage Nvidia’s technological solutions to optimize production processes and enhance both efficiency and sustainability. The human–machine collaboration emphasized by Industry 5.0 will necessitate the reshaping of workforce skillsets and operational approaches.

Finite element (FE) analysis can be used for both design and verification of components. In the case of 3D-printed materials, a proper characterization of properties, accounting for anisotropy and raster angles, can help develop efficient material models. This study aims to use compression tests to characterize short carbon-reinforced PA12 made by fused filament fabrication (FFF) and to model its behaviour by the FE method.

In this work, the authors focus on compression tests, using post-processed specimens to overcome external defects introduced by the FFF process. The material’s elastoplastic mechanical behaviour is modelled by an elastic stiffness matrix, Hill’s anisotropic yield criterion and Voce’s isotropic hardening law, considering the stacking sequence of raster angles. A FE analysis is conducted to reproduce the material’s compressive behaviour through the LS-DYNA software.

The proposed model can capture stress values at different deformation levels and peculiar aspects of deformed shapes until the onset of damage mechanisms. Deformation and damage mechanisms are strictly correlated to orientation and raster angle.

The paper aims to contribute to the understanding of 3D-printed material’s behaviour through compression tests on bulk 3D-printed material. The methodology proposed, enriched with an anisotropic damage criterion, could be effectively used for design and verification purposes in the field of 3D-printed components through FE analysis.

Through a project of cooperation between the Ministry of Heritage and Tourism (MHT) and Sultan Qaboos University (SQU), a team including faculty members, technicians and students from the SQU department of civil and architectural engineering (CAE), was involved in the project of documentation, survey and the development of management plans of four (4) Omani Vernacular settlements (Harat). Such an experience was meant to initiate students from different levels in undergraduate programs of civil and architectural engineering to the fieldwork and professional practice in the field of built heritage studies. The present research aims to explore the effect of such an experience on the learning process and skills acquired by the involved students.

The research was undertaken with students of CAE undergraduate programs at SQU. The documentation method has been implemented in 4 different settlements with the same students. A questionnaire has been administered to the participating students after their graduation to collect their feedback regarding the benefits of this experience on their education and skills development. The data was complemented by active observation and semi-directive interviews with some students randomly selected among the respondents to the questionnaire.

The outcome of each documentation campaign as well as the results of the questionnaires administered revealed that this experience has raised students' awareness about the importance of studying the built heritage and safeguarding it. The research has shown that important soft skills, such as team-working, leadership and communication, have been consolidated. It has also revealed that this experience was an opportunity for students to discover the variety of options within the profession of architecture and its intellectual and ethical responsibilities. Such aspects are hardly grasped when taught within a “classical” teaching/learning setting.

The main limitations of this research were the hard working conditions during the summer in Oman and the direct interaction of the students with the buildings. Even cautious, such interaction represents a risk for an already fragile heritage.

The paper includes a detailed description of the architectural documentation tools and methods used in the case studies. These tools and methods can easily be applicable, with slight adaptations, in other architectural documentation projects involving undergraduate students. The documentation methodology and the generated corpus of 3D digital models can be used in other documentation projects and further studies such as architectural typologies, bioclimatic properties, natural ventilation patterns, daylight performance, etc.

This paper reports on the outcomes of the first experience of its kind in Oman and the Gulf region, where undergraduate students (predominantly females) were involved in an interdisciplinary project for the documentation of important vernacular settlements and their buildings. The added value of this research is that its methodology can be a reference for professors of Architecture and related specialties aiming to integrate research and field work with education.

The tourism industry is undergoing a rapid transformation brought on by artificial intelligence (AI), which is offering a wide range of benefits to both businesses and their customers. Nevertheless, this technological advancement also poses a number of difficulties for which the sector will need to find solutions. This chapter investigates the effects that artificial intelligence (AI) has had on the tourism industry in Europe, with a particular focus on how the hospitality industry has reacted to the advent of this technology. Following an overview of the tourism and hospitality industries in Europe, this chapter begins with an introduction to artificial intelligence (AI) in the tourism industry. The section on the methodology describes the various approaches to research that were utilised in this study, and the section on the conclusion summarises the findings.

This study aimed to improve understanding of the phenomenon of food well-being (FWB) (conceptualization, measurement, antecedents and outcomes) so as to lead future empirical work on measurement, development and theory testing. The hope is to improve the societal benefits of FWB and sustainable food system transformation.

A domain-based systematic review of FWB was conducted using databases (Web of Science, ABI/INFORM, EBSCO and Scopus). The well-established theory, context, characteristics and methodology framework were used to structure the review.

This study synthesized conceptual definitions and measurements of consumer FWB from hedonic, eudemonistic and mixed research streams and a nomological network that distinguishes this construct from its antecedents and outcomes.

This study provides recommendations for consumers, food designers, retailers and policymakers to improve FWB.

This study assessed the conceptualizations of FWB from hedonic, eudemonistic and mixed perspectives for conceptual clarity. It summarized ten measurement tools for FWB-allied concepts (Well-being Related to Food Questionnaires, Satisfaction with Food-Related Life Scale and World Health Organization-Five Well-Being Index), which revealed the need for novel measurement. This study developed a holistic nomological network of FWB by identifying the categories of antecedents (food-related, consumer-related and contextual factors) and outcomes (general well-being, life satisfaction and food consumption). This study provides a research agenda for FWB measurement and theoretical development.