University of Buraimi

PurposeBuilding upon self-regulation theory, this study aims to propose and empirically investigate the relationship of moral judgment, Islamic perceptions of entrepreneurship and perceptions of halal income with Islamic entrepreneurial intentions. This study also proposes the boundary condition of Islamic entrepreneurial self-efficacy.Design/methodology/approachData for the current study is collected from two countries i.e. Oman and Pakistan. Questionnaires have been used to elicit the responses of undergraduate students of both countries. Convenience sampling techniques have been used to approach the respondents.FindingsAnalysis of data reveals that moral judgements, Islamic perceptions of entrepreneurship and perceptions of halal income are related with the Islamic entrepreneurial intentions (IEIs) of respondents from both samples. Islamic entrepreneurial self-efficacy moderates the relationship of all paths for both samples, except the relationship of moral judgment and IEIs of the Omani sample.Originality/valueThe study proposes a novel model of Islamic entrepreneurial intentions, which is built upon the self-regulation theory. The research is scant on this theoretical lens when the author look for entrepreneurial intentions or behavioral perspectives.

The unsteady variations in the near wake of a moving cylinder induce lift and drag forces on it, which are customarily normalized and expressed in terms of nondimensional lift and drag coefficients. While there are already several wake oscillator models for either a fixed or moving cylinder, special attention was given to modeling the lift coefficient for the case of a fixed cylinder or the case of a cylinder with one-degree-of-freedom motion in the cross-stream direction. When the drag coefficient is molded for a fixed or two-degree-of-freedom moving cylinder, a two-to-one frequency relationship (or quadratic coupling) between the drag and lift coefficients was assumed in the literature. However, we report situations of the excited wake of a vibrating cylinder, where such a modeling assumption fails to reproduce the actual pattern of the drag coefficient. We excite the wake of the cylinder by vibrating it harmonically in straight lines, and we then investigate the effect of this mechanical harmonic excitation on the lift-drag coupling using three tools for nonlinear dynamics analysis, namely, (1) time domain, (2) projection of the limit cycle, and (3) power spectra. We perform this analysis under different motion cases with manifested lift-drag coupling types that call on an extended universal drag model that accommodates such cases. Based on this, we propose a new reduced-order drag model with both linear and quadratic coupling terms to the lift as well as a mean component (thus, the proposed model consists of five terms). We verified the accuracy of the proposed reduced-order drag model by testing its ability to reproduce the time-dependent drag coefficient signals at a low Reynolds number of 300. These drag coefficient signals were obtained by applying direct numerical simulation (DNS) to integrate the two-dimensional incompressible Navier–Stokes equations governing the near wake fluid flow, with the aid of the finite difference method (FDM). The proposed drag model helps in extending the wake oscillators to more general cases of fluid–structure interaction (FSI) or vortex-induced vibration (VIV).

Background: The flipped classroom model (FC) has gained prominence in nursing education for its emphasis on active, student-centered learning. While global evidence supports its efficacy in skill-based training such as cardiopulmonary resuscitation (CPR), limited studies have evaluated its impact within Middle Eastern nursing programs, particularly in Oman. Objective: This study aimed to assess the effectiveness of the FC approach in enhancing CPR knowledge, skills, and learner perception among first-year nursing students. Methods:Exploratory quasi-experimental one-group pretest/post-test design was conducted among 177 first-year nursing students enrolled in the Fundamentals of Nursing I course at the University of Buraimi, Oman. Participants completed preclass materials, followed by collaborative case-based discussions and skill demonstrations. CPR knowledge was assessed through multiple-choice tests, skills through a standardized checklist, and perceptions using a validated Likert-scale questionnaire. Results: There was a statistically significant improvement in CPR knowledge scores from pretest (M = 6.81, SD = 3.20) to post-test (M = 10.88, SD = 2.00; p < .001). Knowledge scores moderately correlated with CPR skill performance (r = .209, p = .005), though no significant correlations were found with perception scores. Female students demonstrated significantly higher CPR performance than males (p = .023). Overall, students expressed positive perceptions of the FC model. Conclusion: The FC approach significantly improved CPR knowledge and moderately influenced skill acquisition among novice nursing students, irrespective of academic standing. These findings suggest potential benefits of integrating FC methods but should be interpreted as exploratory within a single-group design. Support the integration of active, student-centered methodologies in nursing education across the Middle East. Further research is recommended to explore long-term retention and clinical application.

Background Fast-food consumption has become increasingly prevalent among university students, contributing to unhealthy dietary patterns and rising obesity rates. Understanding students' fast-food consumption habits, knowledge, and attitudes is essential for designing effective health promotion strategies. Objective To evaluate fast-food consumption habits, knowledge, and attitudes, and to examine their association with Body Mass Index (BMI) among undergraduate students at the College of Health Sciences, University of Buraimi, Oman. Methods A descriptive cross-sectional study was conducted among 222 undergraduate students selected using convenience sampling. Data were collected via an online questionnaire assessing demographics, fast-food consumption patterns, knowledge (11 items), attitudes (9 items), and self-reported anthropometric measures. Data were analyzed using descriptive statistics, t-tests, ANOVA, and multivariable logistic regression. Results Most participants were female (88.7%), single (93.2%), middle-income (60.4%), and aged 20–29 years (58.6%). Burgers (66.2%), pizza (44.1%), and fried chicken (38.3%) were most preferred, consumed primarily at dinner/evening for taste and convenience. Students demonstrated good knowledge (60.4%) and neutral-to-positive attitudes (87.4%), yet 36.5% were overweight/obese and 15.8% underweight. No significant differences in knowledge, attitude, or BMI emerged by gender or year of study (all p > 0.05, small effect sizes). Despite good knowledge and positive attitudes, a substantial proportion of students were overweight/obese, suggesting a potential knowledge–practice gap; however, no statistically significant association was found between knowledge, attitudes, intake frequency, and BMI (p > 0.05). Logistic regression showed that intake frequency, knowledge, attitude, and gender were not significant predictors of obesity (all p > 0.05; Nagelkerke R² = 0.028). Conclusion Despite adequate knowledge and positive attitudes, substantial proportions of students were overweight/obese or underweight. The lack of significant predictors highlights obesity's multifactorial nature and the need for comprehensive, behavior-focused interventions beyond nutritional education in university settings.

Unsupervised clustering has become an attractive solution to personalise the learning with AI-assistance in English without the necessity of labelled results. Standard similarity metrics tend to assess all features of learners in the same way, restricting their capacity to reflect pedagogically significant variations. This work is a continuation that builds on a baseline cosine-similarity clustering model, adding a weighted cosine similarity structure-based clustering framework that enhances the discovery of the persona of learners in learning the English language with the help of artificial intelligence. With the relevant large-scale dataset of 15,000 learner interactions with tools like ChatGPT, Grammarly, Duolingo and ELSA Speak, we experimentally consider various schemes of weighting, where the primary concern is that of learning gain, task engagement and error reduction. The feature weighting that is proposed combines with the common standardised preprocessing and dimensionality reduction feature and allows more expressive similarity modelling with no complexity increase to the model. Numerous clustering methods are compared with the use of weighted and unweighted cosine similarity on the Silhouette score, Davies-Bouldin index and Calinski-Harabasz index, finding significant and consistent improvements on both Euclidean and unweighted cosine baselines, with the ability to produce Silhouette scores up to 0.77 and well-separate and pedagogically interpretable clusters of learners. The refined clusters have a more distinct differentiation in the learning efficiency and task-engagement profiles, which makes them even more appropriate to be used in downstream personalisation and recommendation tasks. Placed in a non-native learning of English in the GCC context, the work contributes to unsupervised learner modelling and gives a solid methodological basis for future adaptive tutoring and chatbot-assisted learning systems.