Ministry of Education and Higher Education

Artificial intelligence has transitioned from a peripheral innovation to a core infrastructure shaping higher education within a remarkably short period. While conceptual debates on AI ethics, pedagogy, and academic integrity are expanding, empirically grounded syntheses that consolidate global evidence remain limited. This study addresses this gap by providing an integrated cross-domain synthesis and statistically grounded overview of AI adoption, use, and governance across higher education systems. Using a secondary statistical synthesis methodology, the study aggregates large-scale quantitative data published between 2021 and 2025 from reputable international sources, including student and faculty surveys, institutional reports, research indices, and regulatory datasets. Results demonstrate near-universal student adoption of AI tools, rapid but uneven professional engagement among faculty and staff, a sharp rise in AI-related academic misconduct, accelerating impacts on research production and scientific workflows, and persistent gaps in institutional preparedness, policy development, and equity. The findings reveal a widening disconnect between bottom-up AI adoption and top-down governance mechanisms, particularly in assessment design, academic integrity frameworks, faculty capacity building, and quality assurance systems. Moreover, this paper argues that AI can no longer be treated as an optional educational technology and must instead be governed as a foundational component of higher education infrastructure. The study concludes by outlining evidence-based policy implications for institutions, regulators, and quality assurance agencies, emphasizing the need for coordinated, adaptive, and equity-oriented governance frameworks grounded in empirical realities rather than speculative narratives.

The interplay between magnetic order, charge dynamics, and crystal field excitations underpins the emergent ground states of rare-earth intermetallics. Using time-domain terahertz spectroscopy, we probe this coupling in PrSi, a metallic ferromagnet. The optical response exhibits pronounced Drude-Smith behavior over a broad temperature range, indicating persistent carrier scattering. A classical Kondo-lattice model (CKLM) attributes this non-Drude conductivity to scattering of itinerant electrons by localized magnetic moments, persisting down to temperatures well below the magnetic ordering scale. At lower temperatures, beyond the scope of CKLM, our experiment reveals that the response is dominated by crystal field excitations, with sharp transitions at 0.6 and 1.54THz. The mode at 1.54THz shows a dynamic correlation with the onset of ferromagnetic order, marking the onset of a crystal-field-governed low temperatureregime.

As businesses become more aware of the importance of emotional intelligence in employee satisfaction and organizational performance, its inclusion in workplace wellness programs has become more popular. This chapter discusses how Emotion AI- powerful technologies that recognize and understand human emotions- can be used to cultivate emotionally intelligent workplaces and positive organizational culture. This chapter theorizes the embedding of Emotion AI into core human resource management, leadership, and workplace communication domains. It explores how these technologies can inform empathetic decision-making, enhance team dynamics, and build inclusive, emotionally supportive cultures. Ethical issues such as data privacy, consent, and algorithmic bias are also deeply scrutinized. This chapter contends that when used carefully and responsibly, Emotion AI has enormous potential to transform cultural well-being and aid in creating emotionally mature, high-performance organizations.

Abstract This paper presents a comprehensive study of right $${\textbf {S}}$$ S -maximal ideals in noncommutative rings, providing a natural extension of classical ideal theory through the framework of $${\textbf {m}}$$ m -systems. We establish deep connections among right $${\textbf {S}}$$ S -maximal, S -comaximal, and $${\textbf {S}}$$ S -prime ideals, and introduce new concepts such as the $${\textbf {S}}$$ S -Jacobson radical and $${\textbf {S}}$$ S -invertible elements to further develop the structural theory of rings. A key contribution is the introduction of $${\textbf {S}}$$ S -local rings and the formulation of an $${\textbf {S}}$$ S -version of Nakayama’s Lemma. In addition, we propose two complementary definitions of left $${\textbf {S}}$$ S -primitive ideals–one ideal-theoretic and the other annihilator-based–and demonstrate their intrinsic relationship to $${\textbf {S}}$$ S -prime ideals. Our results not only unify and generalize existing notions but also open promising avenues for further research, particularly in exploring the interplay between different forms of $${\textbf {S}}$$ S -primitivity.

The notion of weakly [Formula: see text]-absorbing ideals, introduced as a natural generalization of prime ideals, has gained significant attention in commutative rings. A weakly [Formula: see text]-absorbing ideal of a commutative ring [Formula: see text] ensures that for all [Formula: see text], the inclusion [Formula: see text] and [Formula: see text] implies that at least one of [Formula: see text] or [Formula: see text] belongs to [Formula: see text]. This paper builds upon the existing framework by introducing and exploring weakly [Formula: see text]-[Formula: see text]-absorbing ideals in the context of a multiplicatively closed subset [Formula: see text] of [Formula: see text]. An ideal [Formula: see text], disjoint from [Formula: see text], is defined as weakly [Formula: see text]-[Formula: see text]-absorbing if [Formula: see text] and [Formula: see text] guarantee that [Formula: see text], [Formula: see text], or [Formula: see text] for some [Formula: see text]. We give the fundamental properties of weakly [Formula: see text]-[Formula: see text]-absorbing ideals and investigate their behavior under various ring constructions, such as amalgamation duplications, homomorphic images, direct products and trivial extensions. Notable results include conditions under which the ideals retain the weakly [Formula: see text]-[Formula: see text]-absorbing property and characterizations of these ideals in special commutative rings such as reduced rings and local semiprime rings which are not prime.

Internet of Things (IoT) and edge computing convergence has become a new paradigm to promote the development of sustainable agriculture and food systems. Whereas conventional cloud-focused systems can provide large scale data services, they are usually impeded by latency, bandwidth, and connectivity issues especially in rural and constrained-resource target markets. This paper suggests a new IoTcombined edge computing system, which can facilitate real-time observation, predictive decisionmaking, and management with minimal resources, in the agricultural industry. Using multi-sensor fusion, distributed edge intelligence, and cloud-enabled analytics, with this framework, the precision farming is allowed, interventions oriented to climate, and resource utilization optimization. Uzbekistan experiences and other similar situations suggest that this framework can be used to increase agricultural yields, decrease the amount of inputs wasted, and ensure better resilience in food chains.

This research offers a critical reading of the Diwan Aduñada by the Syrian poet Adonis, as this diwan represents a poetic summary of the poet's experience, particularly in confronting life after many years. The central themes of the reading are based on two motivations: first, the motif of the ego, in which the poet is portrayed as the interface of the body that does not die, with its features clarified through the myth that served as a cognitive signifier in Adonis's poetry. Second, the stimulus of memory, where its presence alongside the ego forms the basis of a normative, binding text that is read through various times and eras. Between the manifestation of the ego and the memory, the image emerges as a complement to Adonis's poetic sensibility. The study concludes with a methodological approach of description and analysis, structured around three topics: first, whether memory is a method or a content; second, the ego between the philosophy of myth and the projections of history; and third, memory and the persistent anxiety of the past. The final topic explores the relationship of the image in the formation of the flood of absence.

In this paper, we investigate the solution of the conformable Laplace equation, [Formula: see text] within a D-dimensional space, where the order of the conformable derivative satisfies [Formula: see text]. The conformable scalar potential [Formula: see text] is expressed in terms of the conformable Gegenbauer polynomials. Furthermore, we derive generalized expressions for the Coulomb constant k and the gravitational constant G as functions of the fractional order [Formula: see text]. It is shown that these expressions reduce to their classical values in the limit [Formula: see text], thereby recovering the standard results of classical potential theory.

The increasing incidence of oil contamination in many aquatic ecosystems, particularly in oil-rich regions such as Qatar, poses significant threats to marine life and human activities. Our study addresses the critical need for effective and eco-friendly oil-water separation techniques, focusing on developing graphene and chitosan-based three-dimensional (3D) polymeric sponges. These materials have demonstrated potential due to their high porosity and surface area, which can be enhanced through surface treatment to improve hydrophobicity and oleophilicity. This study introduces a new technique dependent on the optimization of the graphene oxide (GO) concentration within the composite sponge to achieve a superior oil uptake capacity (51.4 g oil/g sponge at 3% GO), and the detailed characterization of the material’s performance in separating heavy oil-water emulsions. Our study seeks to answer key questions regarding the performance of these modified sponges and their scalability for industrial applications. This research directly aligns with Qatar’s environmental goals and develops sustainable oil-water separation technologies. It addresses the pressing challenges of oil spills, ultimately contributing to improved marine ecosystem protection and efficient resource recovery.