Evaluating generative AI integration in Saudi Arabian education: a mixed-methods study.

Incorporating generative artificial intelligence (GAI) in education has become crucial in contemporary educational environments. This research article thoroughly investigates the ramifications of implementing GAI in the higher education context of Saudi Arabia, employing a blend of quantitative and qualitative research approaches. Survey-based quantitative data reveals a noteworthy correlation between educators' awareness of GAI and the frequency of its application. Notably, around half of the surveyed educators are at stages characterized by understanding and familiarity with GAI integration, indicating a tangible readiness for its adoption. Moreover, the study's quantitative findings underscore the perceived value and ease associated with integrating GAI, thus reinforcing the assumption that educators are motivated and inclined to integrate GAI tools like ChatGPT into their teaching methodologies. In addition to the quantitative analysis, qualitative insights from in-depth interviews with educators unveil a rich tapestry of perspectives. The qualitative data emphasizes GAI's role as a catalyst for collaborative learning, contributing to professional development, and fostering innovative teaching practices.

An optimized multi-attribute decision-making approach to construction supply chain management by using complex picture fuzzy soft set.

Supplier selection is a critical decision-making process for any organization, as it directly impacts the quality, cost, and reliability of its products and services. However, the supplier selection problem can become highly complex due to the uncertainties and vagueness associated with it. To overcome these complexities, multi-criteria decision analysis, and fuzzy logic have been used to incorporate uncertainties and vagueness into the supplier selection process. These techniques can help organizations make informed decisions and mitigate the risks associated with supplier selection. In this article, a complex picture fuzzy soft set (cpFSS), a generalized fuzzy set-like structure, is developed to deal with information-based uncertainties involved in the supplier selection process. It can maintain the expected information-based periodicity by introducing amplitude and phase terms. The amplitude term is meant for fuzzy membership, and the phase term is for managing its periodicity within the complex plane. The cpFSS also facilitates the decision-makers by allowing them the opportunity to provide their neutral grade-based opinions for objects under observation. Firstly, the essential notions and set-theoretic operations of cpFSS are investigated and illustrated with examples. Secondly, a MADM-based algorithm is proposed by describing new matrix-based aggregations of cpFSS like the core matrix, maximum and minimum decision value matrices, and score. Lastly, the proposed algorithm is implemented in real-world applications with the aim of selecting a suitable supplier for the provision of required materials for construction projects. With the sensitivity analysis of score values through Pythagorean means, it can be concluded that the results and rankings of the suppliers are consistent. Moreover, through structural comparison, the proposed structure is proven to be more flexible and reliable as compared to existing fuzzy set-like structures.

Assistive technology acceptance for visually impaired individuals: a case study of students in Saudi Arabia.

Assistive technology (AT) helps students who suffer from visual impairments to achieve their study goals; however, AT's adoption in Saudi universities is not yet explored. This paper adopts and then extends the Unified Theory of Acceptance and Use of Technology (UTAUT) to incorporate factors influencing the AT's acceptance based on a designed survey. The survey data was analyzed using Structural Equational Modelling (SEM) with the Partial Least Squares (PLS) technique. The results showed that the factors influencing technology acceptance in this context differed from those previously found to influence acceptance in other contexts. The differences were further studied using post-interview, which shows that the differences are related to limited awareness of visual disability and AT and psychological sensitivity of disabled users in Saudi culture. Moreover, this study provides a list of recommendations for overcoming barriers that limit the acceptance of assistive techniques by Saudi students with visual disabilities. This work's results provide recommendations for the Saudi government and administrators concerning access to assistive technology in universities and facilitate access to other technologies and other contexts.

Cu(ii)-thiophene-2,5-bis(amino-alcohol) mediated asymmetric Aldol reaction and Domino Knoevenagel Michael cyclization: a new highly efficient Lewis acid catalyst.

The highly efficient Lewis acid-catalytic system Cu(ii)-thiophene-2,5-bis(amino-alcohol) has been developed for enantioselective Aldol reaction of isatin derivatives with ketones. The new catalytic system also proved to be highly enantioselective for the one pot three-component Domino Knoevenagel Michael cyclization reaction of substituted isatin with malononitrile and ethylacetoacetate. The chiral ligand (2S,2'S)-2,2'-((thiophene-2,5-diylbis(methylene))bis(azanediyl))bis(3-phenylpropan-1-ol) (L1) in combination with Cu(OAc)2·H2O employed as a new Lewis acid catalyst, furnished 3-substituted-3-hydroxyindolin-2-ones derivatives (3a-s) in good to excellent yields (81-99%) with high enantioselectivities (up to 96% ee) and spiro[4H-pyran-3,3-oxindole] derivatives (6a-l) in excellent yields (89-99%) with high ee (up to 95%). These aldol products and spiro-oxindoles constitute a core structural motif in a large number of pharmaceutically active molecules and natural products.

Developing and evaluating cybersecurity competencies for students in computing programs.

Changes due to technological development in the workplace are putting pressure on academia to keep pace with the changing nature of work. Due to the growing need for cybersecurity professionals, universities improve their cybersecurity programs to develop qualified cybersecurity competencies. The purpose of this study is to validate the cybersecurity knowledge, skills, and abilities (KSAs) competencies of cybersecurity degree programs using a fuzzy linguistic group decision-making method. This study shows that cybersecurity knowledge is essential, along with technical skills and human abilities for cybersecurity professionals.

Exploiting the Chiral Ligands of Bis(imidazolinyl)- and Bis(oxazolinyl)thiophenes-Synthesis and Application in Cu-Catalyzed Friedel-Crafts Asymmetric Alkylation.

Five new C2-symmetric chiral ligands of 2,5-bis(imidazolinyl)thiophene (L1-L3) and 2,5-bis(oxazolinyl)thiophene (L4 and L5) were synthesized from thiophene-2,5-dicarboxylic acid (1) with enantiopure amino alcohols (4a-c) in excellent optical purity and chemical yield. The utility of these new chiral ligands for Friedel-Crafts asymmetric alkylation was explored. Subsequently, the optimized tridentate ligand L5 and Cu(OTf)2 catalyst (15 mol%) in toluene for 48 h promoted Friedel-Crafts asymmetric alkylation in moderate to good yields (up to 76%) and with good enantioselectivity (up to 81% ee). The bis(oxazolinyl)thiophene ligands were more potent than bis(imidazolinyl)thiophene analogues for the asymmetric induction of the Friedel-Crafts asymmetric alkylation.

Causes, timing, and modes of death in a tertiary pediatric intensive care unit: Five years' experience.

OBJECTIVES: To identify the causes, modes, and timing of death in a tertiary pediatric intensive care unit (PICU). METHODS: This is a retrospective data analysis of patients older than 48 hours and younger than 15 years who died in the PICU over a 5-year period from January 2012 until December 2016 at a tertiary hospital in Riyadh, Saudi Arabia. RESULTS: There were 101 deaths out of 2295 admissions, representing average crude mortality rate of 4.4%. Sepsis was the most common cause of death in 31 patients (30.7%), followed by lower respiratory tract infections in 19 (18.8%), and cardiac diseases in 12 (11.9%). Failed cardiopulmonary resuscitation was the most common mode of death in 51 patients (50.5%), followed by withholding life-sustaining treatment in 43 (42.6%), and brain death in 7 (6.9%). Although more deaths occurred during after hours (n=70; 69.3%), there was no significant correlation between mode of death and working hours vs. after hours (p>0.05). Among the cohort, 63 patients (62.4%) had an infection-attributed mortality, of which 43 (68.3%) were bacterial, 14 (22.2%) were viral, and 10 (15.9%) were fungal. CONCLUSION: Infections remain a significant cause of death in the PICU. Further improvement of prevention programs and early therapy of severe infections could lower pediatric mortality. This report highlights the need for enhancing palliative care programs. The low rate of brain death diagnoses warrants further investigation.