American University of the Middle East

This study aims to utilize principal component analysis (PCA) to analyze the effects of various chemical components on the behavior of cementitious composites containing cellulose nanomaterials and basalt fiber pellets (BFP). The PCA approach, representing nearly 80% of the data set’s variance, effectively identified several patterns among the materials. However, the dispersion along the second principal component (PC2), influenced by water (H2O), nanosilica (NS), nanofibrillated cellulose (NFC), and nanocrystalline cellulose (NCC), limits the conclusions that can be drawn. To refine the analysis, a second PCA was conducted, excluding variables with high orthogonality, such as H2O, NS, NCC, and NFC. This refinement increased the total variance explained by 10% and allowed a clearer separation of mechanical properties influenced by BFP and fine aggregates. BFP showed a high correlation with key mechanical properties, such as initial setting time (IST), final setting time (FST), residual strength, toughness (T), and Ri, due to its inherent properties. Fine aggregates were correlated with first peak strength, ductility factor (DF), and compressive strengths at 3 and 28 days (Fc′3d and Fc′28d). The refined PCA approach demonstrated that excluding certain variables highlighted the mechanical features influenced by BFP and fine aggregates, which were not evident in the initial PCA. This method, termed PCA-driven PCA, proved effective in revealing more relevant patterns in the data, underscoring the value of iterative PCA refinements for better understanding the behavior of cementitious composites.

ABSTRACT This study investigates the association between ESG performance and firm market value in the Scandinavian context, which is characterized by relatively mature sustainability institutions. Focusing on publicly listed firms in Scandinavia (Denmark, Norway, and Sweden) over the period 2011–2023, the analysis employs panel data comprising 2223 firm‐year observations and fixed‐effects regression models to examine the effects of ESG on firm market value. Given the institutional maturity of Scandinavian sustainability systems, limited evidence exists on whether ESG remains a value‐relevant strategic differentiator and through which financial channels it affects firm market value. Contrary to conventional expectations, the findings reveal a statistically significant negative association between ESG performance and firm market value, measured by Tobin's Q ratio. However, ESG performance is positively related to profitability, and mediation analysis confirms that profitability partially transmits ESG's influence on firm value. No mediating effect is observed through operational efficiency. These results suggest that in mature sustainability regimes where ESG norms are deeply embedded, ESG performance may cease to operate as a competitive differentiator and instead function as a strategic hygiene factor, drawing on Herzberg's Two‐Factor Theory, in which hygiene factors are necessary baseline conditions rather than sources of differentiation. The study contributes to strategy and sustainability research by showing that the ESG–firm market value relationship may vary across contexts and by highlighting the importance of aligning sustainability initiatives with core value creation mechanisms in the Scandinavian setting.

The assignment of hospital rooms to patients is a critical operational decision that has a direct impact on patient safety, infection control, and staff workload. This study introduces HRPM–IRC, an epidemiology-aware hyper-heuristic framework developed to optimize room–patient matching by minimizing the risk of nosocomial infections, reducing travel and specialty mismatch costs, and promoting equitable nurse workload distribution. A mixed-integer linear programming model is formulated to capture infection transmission probabilities, isolation and cohorting requirements, and multi-ward capacity constraints. On top of this model, a bio-inspired hyper-heuristic adaptively selects and refines low-level heuristics, including cohort-first greedy allocation, risk-gradient swaps, and pathogen-aware local MILP refinement, on the basis of contextual epidemiological indicators and reinforcement learning. The framework was validated using a real-world dataset obtained from a tertiary hospital in Lebanon, comprising 142 anonymized patient admissions, 35 rooms, and six nursing teams. Results demonstrate that HRPM–IRC consistently reduces modeled infection risk and workload imbalance by up to forty percent compared to conventional assignment heuristics while maintaining near-real-time decision-making capabilities suitable for dynamic hospital operations. These findings underscore the effectiveness of epidemiology-aware hyper-heuristics in enhancing hospital resilience, improving infection prevention, and supporting fair resource utilization in data-limited healthcare environments typical of Lebanon and other middle-income countries.

Abstract Background Stroke remains a leading cause of mortality worldwide. Ischemic stroke, caused by arterial occlusion, induces sensorimotor deficits and memory impairments. Excessive activity of the brain angiotensin II type 1 receptor (AT1R) is associated with hypertension and cerebral ischemia. Candesartan (CN), an AT1R blocker, improves cerebrovascular blood flow. Pomegranate ( Punica granatum ) is rich in polyphenolic antioxidants that reduce oxidative stress and inflammation, suggesting potential neuroprotective effects in cerebral ischemia. Aim This study compared the neuroprotective effects of CN administered alone or in combination with pomegranate (POM) in a rat model of cerebral ischemia induced by chronic unilateral carotid artery ligation. Methods Cerebral ischemia was induced by ligation of the right common carotid artery (RCCA) in adult rats. Animals were randomly assigned to four groups: sham control, untreated ischemic, ischemic treated with CN, and ischemic treated with CN + POM. Sensorimotor and cognitive functions were assessed 1–15 days post-surgery using beam balance (BB), beam walking (BW), modified sticky-tape (MST), novel object recognition (NOR), and the Morris water maze (MWM) tests. Results RCCA ligation induced marked sensorimotor deficits and memory impairments. Both CN monotherapy and CN + POM treatment equally restored sensorimotor function to sham-control levels, as demonstrated by BB, BW, and MST tests. In contrast, CN + POM treatment showed greater efficacy than CN alone in improving short-term recognition and spatial memory, as demonstrated by NOR and MWM performance. Conclusion CN effectively reverses ischemia-induced sensorimotor deficits, whereas the addition of POM confers specific and enhanced protection against cognitive impairment, indicating distinct mechanisms underlying sensorimotor and memory recovery after cerebral ischemia.

The ability to model salt-containing deep eutectic solvents (DES) is essential for their rational design and application. Most existing thermodynamic models treat salts as neutral species, neglecting ionic interactions. This work investigates the explicit inclusion of ionic effects in modeling the liquid-phase nonideality of the binary choline chloride (ChCl)/water system. Experimental vapor–liquid equilibrium, solid–liquid equilibrium, water activity, and ChCl activity coefficients obtained from isopiestic measurements were used. Short-range molecular interactions were described with the nonrandom two-liquid (NRTL) model, while long-range ionic interactions were incorporated through the Pitzer–Debye–Hückel (PDH) term. Treating ChCl as a fully dissociated electrolyte and including the PDH contribution significantly improved the representation of nonideality across low and high salt concentrations. These results demonstrate the importance of electrolyte-based modeling frameworks for the development, optimization, and recycling of water-containing DES Types II–IV.

Purpose Applied ethics is critical for preparing engineers to navigate complex technological dilemmas, yet most ethics education research remains focused on Western contexts. This pilot study explores the potential relevance of European sociological and ethical frameworks – including Morin’s “complex thought,” Touraine’s “ethics of the Subject” and Rendtorff’s principles of cosmopolitan ethics – within the unique multicultural environment of Gulf engineering education. Design/methodology/approach A pilot survey of 32 first-year engineering students in Kuwait assessed ethical sensitivity using scenario-based questions aligned with professional codes of conduct. Quantitative and qualitative analyses were conducted, including factor analysis, cluster analysis and gender-disaggregated t-tests. Findings Findings reveal that 51% of students consistently rated unethical behaviors as “very unethical,” with significant gender differences emerging in areas such as gift-giving (p = 0.038) and pilfering organizational resources (p = 0.021). Comparisons with previous Western studies highlight both universal principles and culturally-specific nuances, with gaps identified in competence awareness and collegial support. Research limitations/implications The study’s small sample (*n* = 32) limits generalizability but provides a foundation for longitudinal work. Future research should: (1) expand to Gulf-wide cohorts, (2) track ethical development post-graduation, and (3) compare current data with Western/Asian contexts to test cultural variability. The survey’s prescriptive format may overlook nuanced reasoning; follow-ups should include interviews or vignettes. Theoretical implications include refining Morin’s “reflexive responsibility” for non-Western settings and validating Rendtorff’s cosmopolitan ethics in stakeholder-driven economies. These limitations highlight the need for larger-scale, mixed-methods studies to bridge sociology and applied ethics in engineering education. Practical implications The study proposes actionable reforms: Curriculum: embed ethics across all levels (e.g. link thermodynamics to sustainability ethics); Pedagogy: use gender-sensitive peer mentoring (leveraging female students’ higher Q5/Q11 scores) and stakeholder role-playing (Bonnafous-Boucher and Rendtorff, 2023); assessment: implement ethics audits for senior projects (Jonas’ long-term accountability); Faculty training: address gaps in professors’ ethics instruction (Jutras, 2013). Social implications By cultivating “cosmopolitan engineers” (Rendtorff, 2017a), this research addresses societal challenges in the Gulf’s megaprojects (e.g. AI ethics in smart cities, sustainability in oil/gas). Findings reveal tensions between wasta (nepotism) and global professional standards, suggesting reforms could reduce corruption risks. Gender differences highlight opportunities to leverage women’s ethical leadership in STEM. The framework’s emphasis on reflexive responsibility (Morin) promotes equitable technology deployment, benefiting marginalized communities. If adopted, these recommendations could position Kuwait as a regional leader in ethical engineering education, bridging collectivist traditions with transnational accountability – a model for post-colonial STEM development. Originality/value The study contributes an initial, non-Western exploration of European ethical theory and offers practical strategies for embedding ethics across engineering curricula. It proposes a scaffolded approach – from bachelor’s to PhD levels – that fosters “reflexive responsibility” and aligns with Kuwait’s national vision for sustainable development. This work underscores the value of integrating theoretical depth with empirical insight to cultivate ethically engaged engineers in globalized contexts.

Background/Objectives: Detecting Alzheimer's disease (AD) from normal aging using eyes-open (EO) EEG is challenging due to stimulus-driven nonstationarity and fragmented oscillatory responses. This study aims to determine whether prototype-based representations derived from Dynamic Mode Decomposition (DMD) can improve AD detection from EO photostimulation EEG. Methods: We propose a DMD-based framework termed DMD-based Clustered Pattern Projection (DMD-CPP). Segment-wise DMD representations were clustered to learn class-specific medoid prototypes, and each EEG epoch was encoded as a vector of cosine-similarity coordinates with respect to these prototypes. A linear SVM classifier was trained on the resulting DMD-CPP features and evaluated under strict leave-one-subject-out validation. Results: The DMD-CPP model achieved competitive classification accuracy and, importantly, enhanced margin-based reliability. In EO photostimulation, AD versus healthy control classification showed a pronounced improvement, characterized by wider and more asymmetric decision margins, particularly assigning low confidence to normal epochs misclassified as AD. Tasks involving frontotemporal dementia also showed improvement, although the effect was less pronounced than for AD. Conclusions: Clustering-based pattern projection has been shown to stabilize EEG dynamics and provide an interpretable, confidence-aware feature representation. These findings suggest that DMD-CPP offers a promising framework for reliable AD detection from EO EEG, where conventional spectral methods typically struggle.

ABSTRACT This study investigates the re-entrant magnetic behaviour in a core–shell nanotube structure using Monte Carlo simulations within the framework of the Metropolis algorithm. The system comprises mixed spins, modelled with Blume-Capel interactions under different physical conditions. The temperature dependence of magnetisation and susceptibility is systematically explored by varying the crystal field parameter, exchange couplings and external magnetic field. The results reveal a complex phenomenon of re-entrant magnetisation, where the total magnetisation reverses its sign with temperature changes. For specific values of crystal field and interlayer exchange coupling, the system exhibits multiple sign changes in the sublattice magnetisations and a noticeable compensation point. In addition, the application of a strong external magnetic field suppresses the re-entrant effect due to spin alignment stabilisation. These results highlight the tunability of magnetic properties in core–shell nanostructures, offering potential applications in magnetic storage, spintronics and nanoscale sensors.